Lead Data Engineer ID71008

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Lead Data Engineer to own the data pipeline and analytical architecture layer for a large-volume marketing analytics platform. You will make architectural decisions around partitioning strategy, file formats, schema design, and near-real-time processing for OLAP-oriented workloads built on an S3-backed data lake. You will design and govern ETL pipelines, define DAG-based orchestration strategies using Airflow, drive the AWS data stack including Athena and EKS, and lead a team of senior developers while enforcing code quality standards.

WHAT YOU WILL DO

- Design and own ETL pipelines that extract, transform, and validate data from internal databases and external APIs at scale.

- Make architectural decisions around partitioning, file formats, schema and data-type strategy, and near-real-time processing for large-volume, OLAP-oriented data systems built on an object-storage data lake.

- Own the design of scheduled batch workflows (DAGs) on the client's Airflow setup, defining pipeline structure, dependencies, and triggering strategies, and driving architectural discussions around them.

- Drive the use of the client's AWS data stack, including an S3-backed data lake, Athena, and EKS/Kubernetes.

- Partner directly with the client's DevOps team to clarify functional and non-functional requirements.

- Review pull requests and enforce code quality standards.

- Guide senior developers and ensure alignment with the client's engineering practices.

MUST HAVES

- 7+ years of engineering experience , with a proven track record designing and implementing ETL pipelines and making architectural decisions for large-volume data systems.

- Hands-on experience with OLAP-style analytical data architecture , with experience in Athena, Trino/Presto, BigQuery, Snowflake, Spark SQL, ClickHouse, or similar technologies .

- Hands-on experience designing data lakes backed by object storage such as S3 or equivalent , including partitioning strategies, file formats such as Parquet/ORC, and cost/performance tradeoffs.

- Deep familiarity with DAG-style workflow definition and triggering , with substantial experience in Airflow or comparable orchestrators such as Dagster, Prefect, Luigi, or Step Functions .

- Practical experience across the AWS data ecosystem , including S3-backed data lakes, serverless query engines such as Athena or equivalent, and EKS/Kubernetes.

- Strong backend proficiency in Python , with experience using FastAPI or Flask .

- Comfortable working with REST and GraphQL .

- Experience with Docker and PostgreSQL for transactional and application layers.

- Highly comfortable working in Mac/Linux terminal-centric environments.

- Practical, hands-on experience with AI-assisted development tools such as Claude Code , combined with the critical judgment to challenge AI-generated output when it compromises long-term maintainability.

- Leadership experience setting standards for responsible use of AI tooling, including identifying risky AI-driven shortcuts during code review.

- Strong communication and technical judgment, with the ability to defend technical decisions, challenge quick fixes with sound reasoning, and balance long-term maintainability with pragmatic delivery.

- Upper-Intermediate English level.

NICE TO HAVES

- Direct production experience with Athena.

- Working knowledge of TypeScript and React, sufficient to guide integrations and review frontend-adjacent pull requests.

- Production experience building AI features using AWS Bedrock, LangChain, Pydantic AI, or similar technologies.

- Experience with monorepo tooling such as Nx or modern package managers such as Poetry, UV, or Yarn.

- Experience with Redis and caching layers or SageMaker.

- Experience with marketing data structures, campaign management APIs, or digital advertising metrics.

PERKS AND BENEFITS

- Growth without limits : build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget

- Competitive compensation : get recognition that reflects your skills and impact, with regular performance and compensation reviews

- Flexibility : work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm

- Meaningful, modern projects : build impactful products using modern technologies alongside global teams and leading brands

- Collaborative culture : join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized

- Well-being & support : access local well-being programs and people-focused support tailored to your location