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Data Engineering Manager

  • Data Engineering Manager job type Posted on: Oct 14, 2026
  • Data Engineering Manager experience level Harnham
  • Data Engineering Manager employment type United, Pennsylvania
  • Data Engineering Manager employment type Remote
  • Data Engineering Manager salary Full-time

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Job Title :

Data Engineering Manager

Job Type :

Full-Time

Job Location :

United Pennsylvania United States

Remote :

Yes

Jobcon Logo Job Description :

Job Description

Data Engineering Manager

\n

Location: 100% Remote – US

\n

Level: Lead / Manager

\n


\n

The Opportunity

\n

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.

\n

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.

\n


\n

What You’ll Do

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


\n

What You Bring

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


\n

Nice to Have

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


\n

Why This Role?

\n

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.

Jobcon Logo Position Details

Posted:

Oct 14, 2026

Reference Number:

4d31b36fd981d290

Employment:

Full-time

City:

United

Job Origin:

ziprecruiter

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Job Description

Data Engineering Manager

\n

Location: 100% Remote – US

\n

Level: Lead / Manager

\n


\n

The Opportunity

\n

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.

\n

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.

\n


\n

What You’ll Do

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


\n

What You Bring

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


\n

Nice to Have

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


\n

Why This Role?

\n

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.

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