Data Engineering Manager

Harnham; United States; Teletrabalho; USD 170 000 - 230 000; Tempo integral

Resumo da oferta

Harnham is seeking a senior-level Data Engineering leader to own complex data initiatives and shape a scalable data platform. This hands-on technical leadership role focuses on solving tough data problems, improving engineering standards, and mentoring engineers while staying close to the technology.

You will provide technical leadership across data engineering, design ELT pipelines, own data modeling, and collaborate with cross-functional teams to resolve complex data issues, all while working

Qualificações

• Strong Python experience in data engineering or ELT environments.
• Deep knowledge of data modeling and large-scale transformations.
• Experience designing data ingestion pipelines across multiple sources.
• Hands-on with Airflow or equivalent orchestration framework.
• Experience leading a technical team of ~3–5 engineers.

Responsabilidades

• Provide technical leadership across data engineering, including architecture and code quality.
• Design and build scalable ELT pipelines for data products and analytics.
• Own data modeling, transformations, and integration of new data sources.
• Partner with engineering, product, analytics, and customer teams to resolve complex data issues.
• Lead initiatives from design through deployment and ongoing optimization.
• Improve platform reliability, scalability, automation, and observability.
• Promote best practices around data engineering productivity and maintainability.
• Contribute to technical strategy and evolution of the data platform.
• Mentor and support a team of data engineers.

Conhecimentos

Python

Data modeling

ELT pipelines

Team leadership

Architectural thinking

Ferramentas

Airflow

dbt

Astronomer

Dagster

Descrição da oferta de emprego

We’re looking for a senior-level Data Engineering leader to take ownership of complex data engineering initiatives and help shape a scalable, reliable data platform.

This is a hands‑on technical leadership role for someone who enjoys solving difficult data problems, improving engineering standards, and mentoring other engineers while remaining close to the technology.

What You’ll Do

• Provide technical leadership across data engineering, including architecture, engineering standards, code quality, and technical problem-solving.
• Design and build scalable ELT pipelines supporting data products and analytics.
• Own data modeling, transformations, and integration of new data sources.
• Partner closely with engineering, product, analytics, and customer‑facing teams to resolve complex data and platform issues.
• Lead initiatives from technical design and planning through development, testing, deployment, and ongoing optimization.
• Improve platform reliability, scalability, automation, observability, and overall engineering efficiency.
• Establish and promote best practices around data engineering productivity, quality, and maintainability.
• Contribute to technical strategy and the ongoing evolution of the data platform.
• Mentor and support a team of data engineers, helping raise technical capability and engineering standards.

What You Bring

• Strong Python experience within data engineering or ELT environments.
• Strong understanding of data modeling and large-scale data transformation.
• Experience designing and managing data ingestion pipelines across multiple data sources.
• Hands‑on experience with Airflow or a comparable orchestration framework.
• Experience working with large datasets and inconsistent or complex data quality.
• Previous experience leading or managing a technical team of approximately 3–5 engineers.
• Strong ability to operate at both architectural and hands‑on implementation levels.

Nice to Have

• Experience with dbt.
• Exposure to Astronomer, Dagster, or similar workflow orchestration technologies.
• Experience with MPP / distributed database architectures.
• Healthcare or similarly complex data environments.
• Experience working across multiple database technologies.

Why This Role?

This is an opportunity to have meaningful technical ownership over a growing data platform, influence engineering standards, and make an impact across both architecture and day‑to‑day delivery—all while working remotely within the US.