Senior Data Engineer

We need to produce HTML fragment with sections: About the role? Actually we have "Who We Are", "Position Overview", "Key Responsibilities", "Experience & Seniority", "Education & Certifications", "Technical Skills & Proficiency", "Scope & Impact". We need to map to allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. The instructions: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we should map content to those headings. We must not repeat job title. We must not include Job ID etc. Remove boilerplate. We need to preserve all substantive info. We need to decide which sections to include based on content. We have: - Who We Are: description of company. Could be "About the role"? Actually "About the role" is more about the job, but we could use "About the role" for company overview? Might be okay. Or we could use "About the role" for position overview. The instructions say use those headings as examples, not strict list. Probably we should use headings that match content: About the role (company + position overview), Responsibilities (Key Responsibilities), Requirements (Experience & Seniority + Education & Certifications), Qualifications (maybe Technical Skills & Proficiency), Skills (maybe also Technical Skills). But we need to avoid duplication. Better: Use sections: - About the role: combine Who We Are and Position Overview. - Responsibilities: Key Responsibilities. - Requirements: Experience & Seniority + Education & Certifications (maybe combine). - Skills: Technical Skills & Proficiency. - Scope & Impact could be another section maybe "Impact" but not in list. Could be omitted or put under Responsibilities? But we need to preserve all substantive info. Could create a section "Scope & Impact" but not in allowed headings list. The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It says e.g., meaning those are examples, not exclusive. So we can use other headings if needed, but better to stick to those. However Scope & Impact is substantive; we could incorporate into Responsibilities or About the role. Probably better to add a section "Impact" but not listed; risk. Could use "Qualifications" for Scope & Impact? Not ideal. Maybe we can create sections: About the role, Responsibilities, Requirements, Qualifications, Skills. And embed Scope & Impact within Responsibilities or About the role. Let's extract content: Who We Are: Based in New Jersey and established in 2010, Asset Based Lending, LLC (“ABL”) is one of the nation’s leading Hard Money Lenders. We provide fast bridge financing to real estate investors for the purchase, renovation, or new construction of single family, multi-family and mixed-use properties as well as DSCR rental loans for long term investors. We have closed thousands of loans since we began lending fourteen years ago, producing over $4B in originations. ABL was acquired by a private equity firm in 2021, and with a renewed focus on growth, we’ve set our sights on consistent evolution and cementing our place as the premier private lender in the country. Our Mission is Simple:Make Good LoansProvide Exceptional Service, Every TimeProtect The FirmBuild The Future Position Overview: We are seeking a Senior Data Engineer to own and evolve our enterprise data platform, enabling trusted analytics, regulatory reporting, and AI-ready data at scale. This role will lead the design, implementation, and optimization of our new data lake and data warehouse, integrating multiple internal and external source systems while ensuring strong standards for data quality, governance, security, and reliability. This is a hands-on individual contributor role with significant architectural ownership and technical decision-making authority. The Senior Data Engineer will work closely with Analytics, AI/Data Science, and business stakeholders to translate complex business and regulatory requirements into scalable, compliant, and high-performance data solutions that support ABL’s growth and operational excellence. Key Responsibilities: list bullet points. Experience & Seniority: bullet points. Education & Certifications: bullet points. Technical Skills & Proficiency: bullet points. Scope & Impact: bullet points. We need to output HTML fragment only. We'll structure:

About the role

Who we are paragraph + Position overview paragraph.

Responsibilities

• ... each responsibility

Requirements

Experience & Seniority bullets + Education & Certifications bullets maybe combined.

But better to use

for list. We could split Requirements into two sub-sections? Not needed. We'll make Requirements as
combining both Experience & Seniority and Education & Certifications items.

Skills

Technical Skills & Proficiency items.
We could also add a section "Impact" maybe as

Impact

but not in examples. Could incorporate into Responsibilities. Better to add a separate section "Scope & Impact" as

Scope & Impact

though not in examples but likely acceptable. The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings, but says use those as examples. Safer to stick to those. We could put Scope & Impact under Responsibilities as additional bullet. Let's incorporate Scope & Impact bullets into Responsibilities list. Now we need to ensure we don't include boilerplate like cookie/navigation/legal/EEO etc. There's none. Now produce HTML. We need to preserve all substantive info. Let's extract each bullet. Key Responsibilities bullets: - Own end-to-end design, implementation, and evolution of enterprise data pipelines and core data domains, from source ingestion through analytics and AI-ready datasets - Architect, develop, and optimize scalable ETL/ELT pipelines integrating multiple internal and external source systems - Lead the design and optimization of the data lake and data warehouse to support analytics, regulatory reporting, and operational decision-making - Define and enforce standards for data modeling, testing, deployment, and documentation to ensure long term scalability and maintainability - Implement and maintain data quality, reliability, and observability practices, including automated testing, monitoring, and alerting - Establish and support data governance, metadata management, lineage, and role-based access controls in partnership with business and compliance stakeholders - Design and maintain analytics and ML-ready datasets to support BI, advanced analytics, and future AI/ML initiatives - Apply DevOps and DataOps best practices, including CI/CD, version control, and environment management for data pipelines - Troubleshoot and resolve complex data issues involving legacy systems, custom integrations, and evolving business requirements - Partner closely with Analytics, AI/Data Science, and business leaders to translate complex business and regulatory requirements into robust technical solutions - Provide technical guidance, code reviews, and best practices to junior data engineers and analysts, contributing to a high-quality data engineering practice (no direct people management) - Create and maintain clear, comprehensive documentation for data models, pipelines, architectures, and governance processes to support scalability, knowledge sharing, and operational continuity Experience & Seniority bullets: - Extensive professional experience in data engineering or related roles - Demonstrated experience owning and operating production-grade data platforms in a cloud environment - Proven experience designing and scaling data lakes and data warehouses supporting analytics, reporting, and business critical use cases - Strong ability to translate complex business and regulatory requirements into reliable, maintainable data solutions - Experience operating autonomously as a senior individual contributor with accountability for architecture, quality, and delivery - Senior individual contributor role with no direct people management responsibilities - This role reports to the Analytics & AI/Data Science Lead Education & Certifications bullets: - Bachelor’s degree in computer science, Engineering, or a related quantitative field - Certifications are a plus, and experience with the following cloud platforms: - AWS, Azure, or Google Cloud Platform - Data warehousing or analytics certifications Technical Skills & Proficiency bullets: Programming & Analytics: - Strong proficiency in Python, including PySpark, for data engineering, automation, and pipeline development - Expert-level SQL for analytical modeling, performance tuning, and data warehouse optimization - Deep experience with dbt for transformation, testing, and analytics engineering - Experience supporting BI tools such as Power BI or similar analytics platforms Data & Platform Technologies: - Hands-on experience designing and operating modern cloud data platforms (Snowflake, Databricks, and/or Microsoft Fabric) - Experience building and managing ELT pipelines using tools such as Fivetran, Airbyte, or equivalent technologies - Experience implementing data governance, metadata management, lineage, and access controls using tools such as Collibra or Microsoft Purview Data Engineering & Platform Practices: - Strong foundation in data modeling (dimensional, analytical, and domain-oriented models) - Experience implementing data quality, testing, and observability practices for production data pipelines - Familiarity with CI/CD, version control, and Infrastructure-as-Code concepts applied to data platforms - Solid understanding of security, privacy, and access control considerations in enterprise data environments Scope & Impact bullets: - Significant ownership and technical decision-making authority over the enterprise data platform, including architecture, tooling, standards, and implementation approaches - Direct impact on the reliability, scalability, and compliance of data used for analytics, regulatory reporting, and business decision-making - Acts as a key technical partner to Analytics, AI/Data Science, and business stakeholders, influencing data strategy and execution - Responsible for balancing hands-on delivery with architectural thinking, scalability planning, and long-term platform sustainability - Plays a critical role in establishing and maintaining data quality, governance, security, and access control standards across the organization Now we need to embed Scope & Impact somewhere. Could add as a separate section "Impact" but not in examples. Maybe we can add as a subsection under Responsibilities: after responsibilities list, add another

for Impact? But that would duplicate heading. Better to add a section "Scope & Impact" as

Scope & Impact

and hope it's okay. The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't say you cannot use other headings, just gives examples. I think it's safe. Now produce HTML. We'll wrap paragraphs in

. For lists,

• ...

. Make sure to not include extra whitespace? It's fine. Let's craft. First, About the role paragraph: combine Who We Are and Position Overview. Who We Are paragraph: "Based in New Jersey and established in 2010, Asset Based Lending, LLC (“ABL”) is one of the nation’s leading Hard Money Lenders. We provide fast bridge financing to real estate investors for the purchase, renovation, or new construction of single family, multi-family and mixed-use properties as well as DSCR rental loans for long term investors. We have closed thousands of loans since we began lending fourteen years ago, producing over $4B in originations. ABL was acquired by a private equity firm in 2021, and with a renewed focus on growth, we’ve set our sights on consistent evolution and cementing our place as the premier private lender in the country. Our Mission is Simple: Make Good Loans Provide Exceptional Service, Every Time Protect The Firm Build The Future" Position Overview paragraph: "We are seeking a Senior Data Engineer to own and evolve our enterprise data platform, enabling trusted analytics, regulatory reporting, and AI-ready data at scale. This role will lead the design, implementation, and optimization of our new data lake and data warehouse, integrating multiple internal and external source systems while ensuring strong standards for data quality, governance, security, and reliability. This is a hands-on individual contributor role with significant architectural ownership and technical decision-making authority. The Senior Data Engineer will work closely with Analytics, AI/Data Science, and business stakeholders to translate complex business and regulatory requirements into