ETL Architect / Manager

Job Description

Position Summary

Anchor Loans is seeking a Lead Data Engineer to join our growing Business Intelligence organization. This role will serve as a technical leader and people manager, responsible for the day-to-day execution, prioritization, and delivery of data infrastructure initiatives.

This position will serve as the primary liaison among the Business Intelligence, Data Engineering, and Technology teams, ensuring alignment between business needs and technical execution. The role will report directly to the VP of Business Intelligence. It will play a critical role in scaling Anchor’s data platform, processes, and team capabilities as the business continues to grow.

This is a hands-on leadership role that blends data engineering expertise, stakeholder management, and operational ownership.

Roles & Responsibilities

Essential Duties & Responsibilities

·      Design, build, and maintain scalable, reliable data pipelines and data infrastructure that support Business Intelligence, analytics, and operational reporting.

·      Serve as a hands-on technical lead, spending a significant portion of time writing, reviewing, and deploying production-grade data engineering code.

·      Own end-to-end data ingestion, transformation, and modeling across core business systems, ensuring data is analytics-ready and trustworthy.

·      Lead the day-to-day execution of data engineering work, including task breakdown, prioritization, and delivery, while remaining directly involved in implementation.

·      Identify, design, and implement infrastructure and process improvements, including pipeline automation, performance optimization, monitoring, and cost efficiency.

·      Partner closely with BI analysts and stakeholders to translate business requirements into well-architected technical solutions, not just dashboards.

·      Act as the primary technical liaison between Business Intelligence and Technology teams, proactively resolving data architecture, tooling, and integration challenges.

·      Establish and enforce engineering best practices for data quality, testing, documentation, and version control through direct contribution and code review.

·      Troubleshoot and resolve complex data issues across the stack, performing root cause analysis and implementing long-term fixes.

·      Build and maintain foundational data assets that enable self-service analytics and reduce ad-hoc, manual data work.

·      Provide technical mentorship and guidance to other engineers and analysts through pairing, reviews, and hands-on collaboration, not just oversight.

·      Communicate progress, risks, and architectural tradeoffs clearly to the VP of Business Intelligence, with a focus on execution and outcomes.

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Requirements

·      Bachelor’s degree in computer science, Engineering, or equivalent practical experience.

·      8+ years of experience in data engineering, analytics engineering, or related roles in a cross-functional environment.

·      Demonstrated experience leading projects or teams, formally or informally.

·      Strong expertise in data pipeline architecture, optimization, and reliability.

·      Advanced proficiency in querying relational and/or NoSQL data stores.

·      Experience working with multiple data formats (CSV, JSON, Parquet).

·      Hands-on experience with SQL and NoSQL databases (e.g., Redshift, MySQL, MongoDB).

·      Experience with AWS services such as S3, EC2, and Redshift.

·      Proficiency in Python and orchestration tools such as Airflow.

Preferred, but not required

·      Experience acting as a technical liaison between business and engineering teams.

·      Strong project management and organizational skills; comfortable managing multiple priorities.

·      Experience performing root cause analysis on data and pipeline issues.

·      Familiarity with analytics engineering concepts (data modeling for BI, semantic layers).

·      Experience working with financial, lending, or operational data.

·      Proven ability to operate in a fast-paced, evolving environment and drive clarity through ambiguity.