Senior Data Engineer

We need to output only HTML fragment, using

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, no invention. Remove boilerplate, navigation, legal, EEO, etc. Also remove duplicated lines, application instructions. We need to parse the job description and extract sections. We have: - About the role: description paragraph(s) about role: "MMG Insurance is seeking a Senior Data Engineer to help build, modernize, and maintain the data platforms..." etc. Also travel requirement, location eligibility, etc. Also mention "This role requires consistent travel to our Portsmouth, NH office. Candidates will need to be able to travel to the office in New Hampshire at minimum, monthly. This role is open to candidates residing in ME/NH/MA." Also mention "This role will be responsible for designing and developing scalable data pipelines..." etc. Also mention "This is a modernization role as much as a build role." Also mention "MMG's data estate spans..." etc. Also mention "You will help move that estate onto a governed, version-controlled, automated foundation..." etc. We need to preserve all substantive info, not invent. We need to separate sections: About the role (intro), Responsibilities (list), Requirements (maybe required qualifications), Qualifications (maybe preferred?), Skills (core technologies?), Benefits, Pay, Schedule. But we must only include sections that have real specific content. The posting includes compensation range: "Compensation Range: The anticipated annual compensation range for this position is $115k-$146k." So Pay section can be included. Schedule: Not explicitly mentioned besides travel requirement monthly. There's no explicit schedule like full-time, part-time, remote/hybrid. There's mention "This position is primarily performed in an office or remote work environment and requires prolonged periods of sitting and computer use." That's about work environment, not schedule. No explicit schedule like "40 hours per week". So we should not create Schedule section unless posting actually states them. It does not state schedule, so omit. Benefits: Not mentioned explicitly. There's "Why MMG Insurance" paragraph about investing in modern data infrastructure, opportunity to shape data foundation, etc. Not explicit benefits like health insurance, 401k. So we should not create Benefits section unless posting actually states them. It does not list benefits. So omit. Skills: Could be derived from "Core Technologies Required" and "Preferred". That could be a Skills section. The instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can include Skills if there is real specific content. The posting includes "Core Technologies Required: Python | Databricks | SQL | ETL/ELT | Data Modeling | Git | Cloud Data Platforms Preferred: PySpark | Delta Lake | Azure | Azure Data Factory | Azure AI Foundry | Databricks SQL | CI/CD | APIs | CDC | Data Governance". That's specific. So we can include Skills section. Requirements: Could be "Required Qualifications". That's a list. So we can have Requirements section. Qualifications: Could be "Preferred Qualifications". So we can have Qualifications section. Responsibilities: There's a "Key Responsibilities" bullet list. So we can have Responsibilities. About the role: Intro paragraph(s). So we can have About the role. Pay: Compensation range. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Pay. We must not include Benefits or Schedule. We must not repeat job title as heading. We must not include Job ID/requisition numbers. We must preserve all substantive info; do not invent or summarize away detail. Must not omit any substantive info. So we need to include all details from the posting, but we can reorganize into sections. Must not lose any info. We need to ensure we include travel requirement, location eligibility, etc. Also include "Essential Functions" paragraph maybe part of About the role or Responsibilities? It includes essential functions: designing/building scalable data pipelines, developing/integrating data systems using modern engineering tools and collaborating with cross-functional teams to deliver reliable, high-quality data products while supporting data modernization initiatives. Also mentions duties require ability to analyze, interpret and work with complex data sets, systems, and technical information and ability to communicate and collaborate effectively with technical and non-technical stakeholders. This position is primarily performed in an office or remote work environment and requires prolonged periods of sitting and computer use. The role involves frequent verbal and written communication, participation in virtual and in‑person meetings, and occasional travel to client or company locations. Also accommodation statement. That's substantive; we should preserve it. Where to place? Could be part of About the role or Responsibilities. Since it's about essential functions, maybe include in About the role or Responsibilities. The instruction: preserve ALL substantive information; do NOT invent or summarize away detail. So we need to include that text somewhere. We could add a paragraph under About the role after the intro. We also have "What Success Looks Like" bullet list. That's also substantive; we need to include that. Could be part of Responsibilities or a separate section? Not among allowed headings; but we could incorporate into Responsibilities or About the role. Since we cannot create new headings beyond the allowed list, we need to fit it into existing sections. Probably best to add to Responsibilities (as they are duties/expectations). Or we could add a separate section like "Expectations" but not allowed. So we incorporate into Responsibilities. Also "Core Technologies Required" and "Preferred" list we put into Skills. Also "Compensation Range" we put into Pay. Also "Why MMG Insurance" paragraph we could put into About the role. Also "Essential Functions" paragraph we could put into About the role or Responsibilities. We must not omit any detail. Let's extract all substantive paragraphs and lists. Original text broken down: Job Description MMG Insurance is seeking a Senior Data Engineer to help build, modernize, and maintain the data platforms that support business intelligence, analytics, reporting, and data-driven decision-making across the organization. This role requires consistent travel to our Portsmouth, NH office. Candidates will need to be able to travel to the office in New Hampshire at minimum, monthly. This role is open to candidates residing in ME/NH/MA. This role will be responsible for designing and developing scalable data pipelines and solutions using modern cloud data technologies, with a strong focus on Python, Databricks, SQL, and data engineering best practices. The ideal candidate is a hands-on engineer who can work across teams to understand business needs, translate them into reliable data solutions, and help advance MMG's data engineering capabilities, including modernizing how our legacy IBMi systems connect into the broader data ecosystem. This role will also play a key part in preparing our data platform for data conversion readiness. This is a modernization role as much as a build role. MMG's data estate spans a modern Databricks lakehouse, an established enterprise reporting layer, and legacy ETL and warehouse processes that have grown up over many years. You will help move that estate onto a governed, version-controlled, automated foundation, designing what replaces the manual processes, not only maintaining what exists today. Key Responsibilities Design, build, and maintain scalable, reliable data pipelines and ETL/ELT processes. Develop data engineering solutions using Python, SQL, and Databricks. Build and optimize data pipelines within the Databricks Lakehouse environment. Work with large, complex datasets from multiple sources, including enterprise applications, databases, APIs, and other data platforms. Partner with engineering teams to extract, integrate, and modernize data flows from legacy systems, including IBMi/AS400 environments. Contribute to databricks implementation project and support data platform readiness for large scale data conversion, including data mapping, migration, and integration work. Design and implement change data capture (CDC) patterns to support real-time and incremental data integration. Develop and maintain data models and curate datasets for analytics, reporting, and downstream applications. Implement data quality, validation, monitoring, and error-handling processes. Optimize data pipelines and queries for performance, scalability, reliability, and cost. Partner with data architects, analysts, data scientists, application teams, and business stakeholders to deliver high-quality data solutions. Collaborate with the AI governance group to prepare and structure data for AI/ML pilot programs, including initiatives built on Azure AI Foundry. Participate in the design and evolution of MMG's modern data architecture and engineering practices. Establish and promote standards for code quality, testing, documentation, version control, and deployment. Troubleshoot complex data and pipeline issues and provide sustainable solutions. Contribute to CI/CD and automated deployment practices for data engineering workloads. Mentor other engineers and contribute to the growth of MMG's data engineering capabilities. Required Qualifications Experience establishing version control, testing, review and deployment automation for data Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent professional experience. 5+ years of professional experience in data engineering, software engineering, or a related technical discipline. Strong professional experience with Python and the ability to write clean, maintainable, production-quality code. Strong experience with Databricks, including developing and optimizing data pipelines and workloads. Strong SQL skills and experience working with relational and/or analytical databases. Experience designing and implementing ETL/ELT pipelines and data integration solutions. Experience working with cloud-based data platforms and modern data architectures (Azure preferred). Strong understanding of data modeling, data warehousing, and data lake/lakehouse concepts including medallion / multi-hop architectures. Experience with Git and modern software development practices. Experience with automated testing, deployment, and CI/CD practices. Strong analytical and problem-solving skills. Ability to communicate effectively with both technical and non-technical stakeholders. Preferred Qualifications Experience working in the insurance or financial services industry. Experience integrating data from legacy systems, particularly IBMi/AS400 environments. Experience with Azure AI Foundry or similar AI/ML platform tooling. Experience with Apache Spark / PySpark. Experience with Databricks SQL and Delta Lake. Experience with data orchestration tools such as Azure Data Factory, Airflow, or similar technologies. Experience with APIs and event-driven or real-time data integration. Experience implementing change data capture (CDC) patterns for enterprise data integration. Experience with insurance policy administration platform data or large-scale platform data conversions. Experience with data governance, metadata, lineage, and data quality frameworks. Experience working with enterprise data warehouses and dimensional modeling. Experience with Infrastructure as Code and cloud automation. Experience using AI-assisted development tools to improve engineering productivity. What Success Looks Like In this role, you will: Build reliable, scalable, and maintainable data pipelines that the organization can trust. Help expand MMG's use of Databricks and modern data engineering practices. Improve the availability, quality, and usability of enterprise data. Replace manual and repetitive data processes with automated, monitored pipelines, reducing the operational effort spent correcting and reconciling data by hand. Deliver data solutions that meet both technical requirements and business needs. Help establish consistent engineering standards across the data organization. Serve as a technical leader and mentor for other data engineers. Core Technologies Required: Python | Databricks | SQL | ETL/ELT | Data Modeling | Git | Cloud Data Platforms Preferred: PySpark | Delta Lake | Azure | Azure Data Factory | Azure AI Foundry | Databricks SQL | CI/CD | APIs | CDC | Data Governance Compensation Range: The anticipated annual compensation range for this position is $115k-$146k. This position may be filled at different levels depending on the candidate's experience and qualifications and the final title, level, and compensation will be determined based on the selected candidate's qualifications, experience, skills, and overall fit for the role. Compensation decisions are made in alignment with internal equity and market considerations. Why MMG Insurance MMG Insurance is investing in modern data infrastructure and AI capabilities to support our engineering teams and business operations. This is an opportunity to shape the data foundation for emerging AI pilot programs while working on meaningful, high-impact projects alongside a collaborative