Director, Data & Analytics
for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must include sections only if posting has real specific content. We have content for About the role (intro paragraphs). Responsibilities (list). Requirements (list). Qualifications? The posting includes "Requirements" and also mentions "Physical & Office/Site Presence Requirements". Could treat that as part of Requirements or separate? Probably combine under Requirements. Benefits: there is a "Life at Lennar" section describing benefits. So include Benefits section. Pay: not mentioned. Schedule: not mentioned (though mentions regular in-person attendance). No explicit schedule like full-time, hours. So we should not include Pay or Schedule sections. Also we should not repeat job title as heading. No Job ID. Remove boilerplate: EEO, equal opportunity, scam warning, application instructions, navigation, cookie, legal. Also remove "Visit Lennartotalrewards.com..." and social media links. Also remove "Life at Lennar" heading? We'll use Benefits heading and put the benefits description there. Also we need to preserve all substantive info. Ensure we don't invent.
We need to use - for any list of duties/requirements/benefits. For prose use
. For section headings use
. We'll produce something like:
About the role
... intro paragraphs ...
Responsibilities
- ...
...
Requirements
- ...
...
Benefits
- ...
...
We need to ensure we don't include filler like "commensurate with experience". Not present.
We need to extract the responsibilities list from the "Your Responsibilities" section. It's a long paragraph with sentences separated by periods. We need to turn each duty into a - . The text includes many sentences; we can split by periods that end a sentence. But we need to preserve all substantive info; we can just keep the paragraph as
? The instruction says use
- for any list of duties/requirements/benefits. So we should convert each duty into list items. However the responsibilities are written as a paragraph with many sentences; we can treat each sentence as a list item. That may be many items but okay.
Similarly for Requirements: list of bullet-like sentences separated by periods. We'll split.
Benefits: list of benefits described in paragraph; we can split into list items.
We must be careful not to lose details.
Let's extract sections.
First, About the role: The intro before "Your Responsibilities". It includes:
"Director, Data Engineering We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States. A Career that Empowers You to Build Your Future The Director of Data Engineering leads a team of data engineers, analysts, and data scientists to deliver high-impact data insights that drive strategic business decisions and shape organizational strategy. This role is responsible for setting and driving the overarching strategic vision for the analytics function across the organization. The Director oversees enterprise-wide operations, ensuring alignment with long-term business goals and influencing senior leadership on data-driven decision-making at the highest level. This position involves collaborating with senior executives to integrate business strategies with large-scale analytics initiatives and shaping the strategic direction of data efforts. The Director provides leadership to senior managers and team leads, focusing on strategic mentorship and development to drive innovation and excellence across the teams. They are accountable for defining and implementing organization-wide performance metrics, leading major data initiatives with significant impact, and ensuring alignment with broad business objectives. In addition to overseeing complex, cross-functional projects, the Director is pivotal in shaping data governance policies and ensuring the scalability and strategic alignment of analytics capabilities. They play a critical role in driving organizational change through data and are expected to lead transformative initiatives that enhance the company’s competitive advantage and long-term success. A career with purpose.A career built on making dreams come true.A career built on building zero defect homes, cost management, and adherence to schedules."
We need to keep that as prose. Could be multiple
but we can combine into one
. Ensure we keep all sentences.
Now Responsibilities: The text after "Your Responsibilities" starts with "On The Team Lead, mentor, and develop a team of data engineers, analysts, and scientists, ensuring alignment with organizational goals.Foster a collaborative and innovative team culture, promoting continuous learning and professional growth.Oversee the planning, execution, and delivery of data and analytics projects, ensuring they are completed on time, within scope, and meet business requirements.Prioritize and allocate resources effectively to meet project demands, balancing short-term needs with long-term strategic objectives.Collaborate with cross-functional teams to identify and translate business needs into actionable analytics projects.Act as the primary point of contact for stakeholders, ensuring clear communication and alignment on project goals and outcomes.Ensure adherence to data governance policies, standards, and regulatory requirements, maintaining the integrity and security of data.Implement and enforce best practices for data management, quality, and privacy within the team.Track and report on key performance indicators (KPIs) for the team's projects and initiatives, ensuring alignment with business objectives.Provide regular updates to senior leadership on the progress and impact of analytics efforts.Contribute to the strategic direction of the data and analytics function by identifying new opportunities for leveraging data to drive business value.Stay updated on industry trends and emerging technologies, applying innovative approaches to enhance the team's capabilities.Continuously evaluate and improve processes, tools, and methodologies to increase the team's efficiency and effectiveness.Ensure that the team's operations are streamlined and aligned with overall business priorities.Own the Product Org data platform strategy, including the ingestion architecture, the warehouse relationship, and the data contracts the product applications depend on.Lead the data engineering team that owns ingestion, transformation, and delivery of Product Org data into the applications and reporting surfaces that consume it.Contribute directly as an individual contributor, writing production code, reviewing pipeline design, and taking on delivery work alongside the team.Set the standards for data contracts, schema evolution, and backfill and recovery procedures across consuming product teams, and hold the line that pipeline changes are made through configuration and declarative SQL rather than by forking engine code.Own data platform cost and capacity planning, including compute tiering and warehouse spend, in partnership with Lennar Technology Group.Represent Product Org data needs with Data@Lennar, Lennar Technology Group, and Palantir Foundry stakeholders, and negotiate the contracts for upstream sources.Set the organization’s approach to AI-assisted data engineering, including tooling, review standards, and how quality is measured at high delivery volume.Lead and grow a single data engineering team, including hiring, leveling, and the engineering practices it runs on. Associates in this role typically have a high degree of autonomy in managing their team and projects. They are responsible for making decisions on resource allocation, project prioritization, and team development without needing direct supervision. They collaborate closely with senior leadership and provide inputs for strategic direction and stakeholder alignment; they have the authority to shape the day-to-day operations and long-term plans of their team. This autonomy allows them to respond quickly to changing business needs and drive continuous improvement within the data and analytics function. Stakeholder management is a key aspect of this role, associates in this role are expected to engage, influence and support key technical and non-technical stakeholders."
We need to split into list items. Each sentence ends with a period. We'll create
- for each sentence. Ensure we keep the content exactly.
Let's manually split:
1. Lead, mentor, and develop a team of data engineers, analysts, and scientists, ensuring alignment with organizational goals.
2. Foster a collaborative and innovative team culture, promoting continuous learning and professional growth.
3. Oversee the planning, execution, and delivery of data and analytics projects, ensuring they are completed on time, within scope, and meet business requirements.
4. Prioritize and allocate resources effectively to meet project demands, balancing short-term needs with long-term strategic objectives.
5. Collaborate with cross-functional teams to identify and translate business needs into actionable analytics projects.
6. Act as the primary point of contact for stakeholders, ensuring clear communication and alignment on project goals and outcomes.
7. Ensure adherence to data governance policies, standards, and regulatory requirements, maintaining the integrity and security of data.
8. Implement and enforce best practices for data management, quality, and privacy within the team.
9. Track and report on key performance indicators (KPIs) for the team's projects and initiatives, ensuring alignment with business objectives.
10. Provide regular updates to senior leadership on the progress and impact of analytics efforts.
11. Contribute to the strategic direction of the data and analytics function by identifying new opportunities for leveraging data to drive business value.
12. Stay updated on industry trends and emerging technologies, applying innovative approaches to enhance the team's capabilities.
13. Continuously evaluate and improve processes, tools, and methodologies to increase the team's efficiency and effectiveness.
14. Ensure that the team's operations are streamlined and aligned with overall business priorities.
15. Own the Product Org data platform strategy, including the ingestion architecture, the warehouse relationship, and the data contracts the product applications depend on.
16. Lead the data engineering team that owns ingestion, transformation, and delivery of Product Org data into the applications and reporting surfaces that consume it.
17. Contribute directly as an individual contributor, writing production code, reviewing pipeline design, and taking on delivery work alongside the team.
18. Set the standards for data contracts, schema evolution, and backfill and recovery procedures across consuming product teams, and hold the line that pipeline changes are made through configuration and declarative SQL rather than by forking engine code.
19. Own data platform cost and capacity planning, including compute tiering and warehouse spend, in partnership with Lennar Technology Group.
20. Represent Product Org data needs with Data@Lennar, Lennar Technology Group, and Palantir Foundry stakeholders, and negotiate the contracts for upstream sources.
21. Set the organization’s approach to AI-assisted data engineering, including tooling, review standards, and how quality is measured at high delivery volume.
22. Lead and grow a single data engineering team, including hiring, leveling, and the engineering practices it runs on.
23. Associates in this role typically have a high degree of autonomy in managing their team and projects.
24. They are responsible for making decisions on resource allocation, project prioritization, and team development without needing direct supervision.
25. They collaborate closely with senior leadership and provide inputs for strategic direction and stakeholder alignment; they have the authority to shape the day-to-day operations and long-term plans of their team.
26. This autonomy allows them to respond quickly to changing business needs and drive continuous improvement within the data and analytics function.
27. Stakeholder management is a key aspect of this role, associates in this role are expected to engage, influence and support key technical and non-technical stakeholders.
Now Requirements: The section after "Requirements" starts with "Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field. A master’s degree or equivalent advanced qualifications are highly preferred.Advanced certifications in data analytics, data management, or project management (e.g., Certified Analytics Professional (CAP), Project Management Professional (PMP), or other relevant advanced certifications) are highly advantageous.Extensive expertise in quantitative analysis, data manipulation, and the strategic application of data to drive organizational goals.10+ years of experience in data analytics, data science, or a related field, with a significant portion in senior or leadership roles overseeing complex, high-impact projects.
. For section headings use
. We'll produce something like:
About the role
... intro paragraphs ...
Responsibilities
- ... ...
Requirements
- ... ...
Benefits
- ... ...
? The instruction says use
- for any list of duties/requirements/benefits. So we should convert each duty into list items. However the responsibilities are written as a paragraph with many sentences; we can treat each sentence as a list item. That may be many items but okay.
Similarly for Requirements: list of bullet-like sentences separated by periods. We'll split.
Benefits: list of benefits described in paragraph; we can split into list items.
We must be careful not to lose details.
Let's extract sections.
First, About the role: The intro before "Your Responsibilities". It includes:
"Director, Data Engineering We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities, and Associates by building quality homes and providing exceptional customer service, giving back to the communities in which we work and live in, and fostering a culture of opportunity and growth for our Associates throughout their career. Lennar has been recognized as a Fortune 500® company and consistently ranked among the top homebuilders in the United States. A Career that Empowers You to Build Your Future The Director of Data Engineering leads a team of data engineers, analysts, and data scientists to deliver high-impact data insights that drive strategic business decisions and shape organizational strategy. This role is responsible for setting and driving the overarching strategic vision for the analytics function across the organization. The Director oversees enterprise-wide operations, ensuring alignment with long-term business goals and influencing senior leadership on data-driven decision-making at the highest level. This position involves collaborating with senior executives to integrate business strategies with large-scale analytics initiatives and shaping the strategic direction of data efforts. The Director provides leadership to senior managers and team leads, focusing on strategic mentorship and development to drive innovation and excellence across the teams. They are accountable for defining and implementing organization-wide performance metrics, leading major data initiatives with significant impact, and ensuring alignment with broad business objectives. In addition to overseeing complex, cross-functional projects, the Director is pivotal in shaping data governance policies and ensuring the scalability and strategic alignment of analytics capabilities. They play a critical role in driving organizational change through data and are expected to lead transformative initiatives that enhance the company’s competitive advantage and long-term success. A career with purpose.A career built on making dreams come true.A career built on building zero defect homes, cost management, and adherence to schedules."
We need to keep that as prose. Could be multiple
but we can combine into one
. Ensure we keep all sentences. Now Responsibilities: The text after "Your Responsibilities" starts with "On The Team Lead, mentor, and develop a team of data engineers, analysts, and scientists, ensuring alignment with organizational goals.Foster a collaborative and innovative team culture, promoting continuous learning and professional growth.Oversee the planning, execution, and delivery of data and analytics projects, ensuring they are completed on time, within scope, and meet business requirements.Prioritize and allocate resources effectively to meet project demands, balancing short-term needs with long-term strategic objectives.Collaborate with cross-functional teams to identify and translate business needs into actionable analytics projects.Act as the primary point of contact for stakeholders, ensuring clear communication and alignment on project goals and outcomes.Ensure adherence to data governance policies, standards, and regulatory requirements, maintaining the integrity and security of data.Implement and enforce best practices for data management, quality, and privacy within the team.Track and report on key performance indicators (KPIs) for the team's projects and initiatives, ensuring alignment with business objectives.Provide regular updates to senior leadership on the progress and impact of analytics efforts.Contribute to the strategic direction of the data and analytics function by identifying new opportunities for leveraging data to drive business value.Stay updated on industry trends and emerging technologies, applying innovative approaches to enhance the team's capabilities.Continuously evaluate and improve processes, tools, and methodologies to increase the team's efficiency and effectiveness.Ensure that the team's operations are streamlined and aligned with overall business priorities.Own the Product Org data platform strategy, including the ingestion architecture, the warehouse relationship, and the data contracts the product applications depend on.Lead the data engineering team that owns ingestion, transformation, and delivery of Product Org data into the applications and reporting surfaces that consume it.Contribute directly as an individual contributor, writing production code, reviewing pipeline design, and taking on delivery work alongside the team.Set the standards for data contracts, schema evolution, and backfill and recovery procedures across consuming product teams, and hold the line that pipeline changes are made through configuration and declarative SQL rather than by forking engine code.Own data platform cost and capacity planning, including compute tiering and warehouse spend, in partnership with Lennar Technology Group.Represent Product Org data needs with Data@Lennar, Lennar Technology Group, and Palantir Foundry stakeholders, and negotiate the contracts for upstream sources.Set the organization’s approach to AI-assisted data engineering, including tooling, review standards, and how quality is measured at high delivery volume.Lead and grow a single data engineering team, including hiring, leveling, and the engineering practices it runs on. Associates in this role typically have a high degree of autonomy in managing their team and projects. They are responsible for making decisions on resource allocation, project prioritization, and team development without needing direct supervision. They collaborate closely with senior leadership and provide inputs for strategic direction and stakeholder alignment; they have the authority to shape the day-to-day operations and long-term plans of their team. This autonomy allows them to respond quickly to changing business needs and drive continuous improvement within the data and analytics function. Stakeholder management is a key aspect of this role, associates in this role are expected to engage, influence and support key technical and non-technical stakeholders." We need to split into list items. Each sentence ends with a period. We'll create
- for each sentence. Ensure we keep the content exactly. Let's manually split: 1. Lead, mentor, and develop a team of data engineers, analysts, and scientists, ensuring alignment with organizational goals. 2. Foster a collaborative and innovative team culture, promoting continuous learning and professional growth. 3. Oversee the planning, execution, and delivery of data and analytics projects, ensuring they are completed on time, within scope, and meet business requirements. 4. Prioritize and allocate resources effectively to meet project demands, balancing short-term needs with long-term strategic objectives. 5. Collaborate with cross-functional teams to identify and translate business needs into actionable analytics projects. 6. Act as the primary point of contact for stakeholders, ensuring clear communication and alignment on project goals and outcomes. 7. Ensure adherence to data governance policies, standards, and regulatory requirements, maintaining the integrity and security of data. 8. Implement and enforce best practices for data management, quality, and privacy within the team. 9. Track and report on key performance indicators (KPIs) for the team's projects and initiatives, ensuring alignment with business objectives. 10. Provide regular updates to senior leadership on the progress and impact of analytics efforts. 11. Contribute to the strategic direction of the data and analytics function by identifying new opportunities for leveraging data to drive business value. 12. Stay updated on industry trends and emerging technologies, applying innovative approaches to enhance the team's capabilities. 13. Continuously evaluate and improve processes, tools, and methodologies to increase the team's efficiency and effectiveness. 14. Ensure that the team's operations are streamlined and aligned with overall business priorities. 15. Own the Product Org data platform strategy, including the ingestion architecture, the warehouse relationship, and the data contracts the product applications depend on. 16. Lead the data engineering team that owns ingestion, transformation, and delivery of Product Org data into the applications and reporting surfaces that consume it. 17. Contribute directly as an individual contributor, writing production code, reviewing pipeline design, and taking on delivery work alongside the team. 18. Set the standards for data contracts, schema evolution, and backfill and recovery procedures across consuming product teams, and hold the line that pipeline changes are made through configuration and declarative SQL rather than by forking engine code. 19. Own data platform cost and capacity planning, including compute tiering and warehouse spend, in partnership with Lennar Technology Group. 20. Represent Product Org data needs with Data@Lennar, Lennar Technology Group, and Palantir Foundry stakeholders, and negotiate the contracts for upstream sources. 21. Set the organization’s approach to AI-assisted data engineering, including tooling, review standards, and how quality is measured at high delivery volume. 22. Lead and grow a single data engineering team, including hiring, leveling, and the engineering practices it runs on. 23. Associates in this role typically have a high degree of autonomy in managing their team and projects. 24. They are responsible for making decisions on resource allocation, project prioritization, and team development without needing direct supervision. 25. They collaborate closely with senior leadership and provide inputs for strategic direction and stakeholder alignment; they have the authority to shape the day-to-day operations and long-term plans of their team. 26. This autonomy allows them to respond quickly to changing business needs and drive continuous improvement within the data and analytics function. 27. Stakeholder management is a key aspect of this role, associates in this role are expected to engage, influence and support key technical and non-technical stakeholders. Now Requirements: The section after "Requirements" starts with "Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field. A master’s degree or equivalent advanced qualifications are highly preferred.Advanced certifications in data analytics, data management, or project management (e.g., Certified Analytics Professional (CAP), Project Management Professional (PMP), or other relevant advanced certifications) are highly advantageous.Extensive expertise in quantitative analysis, data manipulation, and the strategic application of data to drive organizational goals.10+ years of experience in data analytics, data science, or a related field, with a significant portion in senior or leadership roles overseeing complex, high-impact projects.