Data Domain Lead Engineer (Hybrid, Databricks/AWS)

Eightelevengroup

New York (NY)

Hybrid

USD 135,000 - 166,000

Full time

11 days ago

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Job summary

Eight Eleven Group in New York, NY is seeking a Data Engineer - Domain Lead to own end-to-end data delivery for a core domain within a growing enterprise data team. You will work hybrid, hands-on with Databricks on AWS, building pipelines from source through bronze and silver to gold layers and delivering outputs to S3.

You will mentor offshore engineers, collaborate with BI and data architecture, ensure domain models align with enterprise standards, and help troubleshoot data quality and

Qualifications

  • 5+ years of experience as a data engineer with mentoring responsibilities.
  • Hands-on Databricks and medallion architecture (bronze/silver/gold).
  • Experience with AWS; Snowflake or similar data warehouses is a plus.
  • Strong SQL and domain-level data modeling.

Responsibilities

  • Own end-to-end data delivery from source to bronze/silver with gold outputs to S3.
  • Lead offshore data/BI engineering resource supporting the domain.
  • Align domain data structures to enterprise data model.
  • Partner with BI engineering on semantic layers and reporting.
  • Track work in Jira or Azure DevOps.
  • Maintain consistency across the data platform.
  • Troubleshoot data quality and pipeline issues.
  • Support inclusive work culture.

Skills

SQL
Data modeling
Mentoring offshore
Domain delivery
Communication
Ownership

Tools

Databricks
AWS
Jira/Azure DevOps
Snowflake

Job description

Eight Eleven Group in New York, NY is seeking a Data Engineer - Domain Lead to own end-to-end data delivery for a core domain within a growing enterprise data team. You will work hybrid, hands-on with Databricks on AWS, building pipelines from source through bronze and silver to gold layers and delivering outputs to S3.

You will mentor offshore engineers, collaborate with BI and data architecture, ensure domain models align with enterprise standards, and help troubleshoot data quality and

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