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Design and assemble scalable data pipelines for consistent data movement across platforms
Build and maintain ingestion processes from numerous distinct source systems
Track pipeline performance and fix problems proactively
Identify and resolve data quality issues
Review code and document technical processes for knowledge transfer
Design and assemble scalable data pipelines that support consistent, dependable data movement across various platforms
Construct and maintain ingestion processes that draw data from numerous distinct source systems
Track the performance of data pipelines, intervening proactively to address problems and sustain overall system reliability
Identify and resolve data quality issues to protect the accuracy and consistency of datasets
Take part in code review activities to help uphold quality standards and distribute knowledge across the broader team
We're growing our team and seeking a Lead Data Software Engineer to join us. This opportunity suits someone who finds fulfillment in building robust data frameworks that drive critical organizational decisions. You'll be embedded in a team that places high value on clean, rigorously tested code paired with disciplined engineering methods. If large-scale data challenges motivate you, this role offers significant room for professional development and impactful work Responsibilities Design and assemble scalable data pipelines that support consistent, dependable data movement across various platforms Construct and maintain ingestion processes that draw data from numerous distinct source systems Deliver clean, efficient, rigorously tested code built on strong software engineering foundations Collaborate with teams spanning different functions to grasp data requirements and translate them into functioning technical solutions Track the performance of data pipelines, intervening proactively to address problems and sustain overall system reliability Take part in code review activities to help uphold quality standards and distribute knowledge across the broader team Identify and resolve data quality issues to protect the accuracy and consistency of datasets Support ongoing improvements to data architecture approaches and engineering best practices Produce documentation detailing technical processes and solutions, supporting knowledge transfer and onboarding of new team members Function within an agile setup, contributing to sprint planning and other regular team rituals Requirements A minimum of 5 years of applicable hands-on experience At least one year spent leading and overseeing development teams Strong working knowledge of PySpark and Spark SQL for building and handling large-scale data processes Experience constructing and managing Lakeflow pipelines and Jobs to enable data orchestration Capable in applying Auto Loader and JDBC/CDC ingestion techniques, including work with sources such as DB2 and SQL Server Solid background with Delta Lake and Unity Catalog, supporting data storage and governance functions Background upholding data quality standards and conducting source reconciliation to guarantee reliable, accurate data Experience crafting unit tests via pytest to verify code accuracy and dependability Working familiarity with Git and Asset Bundles for overseeing version control and deployment processes Upper-intermediate English language skills or higher (B2) Nice to have Background involved in DataStage migration projects Experience pulling data from Dynamics 365/Dataverse Possession of a Databricks certification
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From 10,736 similar postings that came down. Coming down is not always a hire.
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Yes. We’ve followed 15 other Lead Data Software Engineer jobs there since November 2026. All 15 are still up.
Large employers often post one title for several teams, so these can be separate openings.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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