Senior Manager, Data Engineering

New

PalmettoConsumer energy

Remote - United StatesFull-TimeManager

Salary214,000 - 302,000 USD per year

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Job Details

Experience: 10+ years in software or data engineering, including 5+ years managing engineers.
Required Skills: PythonSQLSnowflakeData engineeringData modelingBigQuerydbt

Bring 10+ years of experience in software or data engineering, including 5+ years managing engineers.
Demonstrate a record of hiring well, developing people, and building strong teams.
Have designed enterprise data architecture covering warehouse, modeling, lineage, and governance, and have led architecture reviews.
Bring hands-on experience with a modern warehouse and transformation framework, such as Snowflake, BigQuery, or dbt, and SQL.
Have sufficient fluency in a backend language such as Python to review and contribute to code.
Demonstrate agentic engineering beyond prompting, including using coding agents and bringing agentic practices to a team.
Have working knowledge of production APIs, authorization and access control, and PII handling.
Have delivered data platform projects spanning multiple teams, including decisions about what not to build.
Have a history of building consensus with partners outside engineering, including finance, capital markets, and accounting.
Have experience preparing governed data for AI consumers, with answers traceable to source.
Have experience evaluating vendors and negotiating contracts.

Hire, develop, and retain data engineers; set expectations, provide feedback, and build career paths.
Set the team roadmap in line with company objectives, weigh trade-offs, and deliver cross-team projects on time and on budget.
Set the target architecture for data ingestion, modeling, the semantic layer, and governance.
Review architecture and design proposals and write code when helpful.
Ensure reliable pipelines with clear SLAs, consistent metric definitions, and agent-ready data traceable to source.
Set priorities and standards for the secure data serving layer and APIs.
Evaluate data platform and tooling vendors, negotiate and sign contracts within the approval limit, and manage costs.
Partner with finance, operations, sales, marketing, and product to understand data needs and make recommendations.

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