Frederick Fox

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Senior Data EngineerFull time remote What You'll Do This is not a generalist data role. You will own end-to-end delivery of large-scale batch and streaming data pipelines on AWS, and play a central part in building and maturing a data mesh that powers ML, analytics, and product engineering across the organization. We want engineers who can talk tradeoffs, not just run jobs •     Design and build batch and streaming data pipelines supporting automated data ingestion, ML feature engineering, and analytics across multiple product domains•     Own full-cycle delivery of complex data initiatives: architecture, implementation, testing, deployment, monitoring, and documentation•     Partner with cross-functional teams (Data Science, Product, Engineering) to onboard data products onto the data mesh and ensure data is reliable, performant, and consumable downstream•     Optimize cost, performance, and reliability of large-scale data workloads•     Automate data operations: validation, quality checks, alerting, backfills, and recovery workflows•     Evaluate and adopt new technologies to keep the platform modern and efficient What You Bring (required) •     5+ years of hands-on data engineering experience building and maintaining production-grade pipelines and platforms•     Deep, hands-on expertise with Apache Spark (Python and/or Scala) including performance tuning and optimization•     Proven experience building data solutions on AWS: EMR, Lambda, S3•     Strong track record building both batch and streaming data ingestion pipelines at scale•     Solid foundation in data modeling and schema design for large-scale datasets (partitioning, warehouse concepts)•     Experience operating production pipelines: monitoring, alerting, incident response, reliability improvements•     Software engineering fundamentals: version control, CI/CD, testing strategies, code review•     SQL proficiency for data analytics

Senior Data Engineer

Full time remote

What You'll Do

This is not a generalist data role. You will own end-to-end
delivery of large-scale batch and streaming data pipelines on
AWS, and play a central part in building and maturing a data mesh
that powers ML, analytics, and product engineering across the
organization. We want engineers who can talk tradeoffs, not just
run jobs

• Design and build batch and streaming data pipelines
supporting automated data ingestion, ML feature engineering, and
analytics across multiple product domains

• Own full-cycle delivery of complex data initiatives:
architecture, implementation, testing, deployment, monitoring,
and documentation

• Partner with cross-functional teams (Data Science, Product,
Engineering) to onboard data products onto the data mesh and
ensure data is reliable, performant, and consumable downstream

• Optimize cost, performance, and reliability of large-scale
data workloads

• Automate data operations: validation, quality checks,
alerting, backfills, and recovery workflows

• Evaluate and adopt new technologies to keep the platform
modern and efficient

What You Bring (required)

• 5+ years of hands-on data engineering experience building
and maintaining production-grade pipelines and platforms

• Deep, hands-on expertise with Apache Spark (Python and/or
Scala) including performance tuning and optimization

• Proven experience building data solutions on AWS: EMR,
Lambda, S3

• Strong track record building both batch and streaming data
ingestion pipelines at scale

• Solid foundation in data modeling and schema design for
large-scale datasets (partitioning, warehouse concepts)

• Experience operating production pipelines: monitoring,
alerting, incident response, reliability improvements

• Software engineering fundamentals: version control, CI/CD,
testing strategies, code review

• SQL proficiency for data analytics

Socure Senior Data Engineer cheat sheet.docx

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Joe Watts

Active - OPEN

Senior Data Engineer | 4 openings | remote from NYC, SF Bay Area or Seattle metro areas

Senior Data Engineer | 4 openings | remote from NYC, SF Bay Area or Seattle metro areas

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