Senior Data Engineer

SocureSeattle, WA

About The Position

We are looking for a Senior Data Engineer to join our Data Automation team. You will play a critical role in designing and building scalable data platforms and pipelines that power Socure’s identity verification products and analytics. This role is ideal for someone who has a strong passion for solving real business problems with data, and combines deep hands-on data engineering expertise with strong ownership.

Requirements

  • 5+ years of hands-on data engineering experience, building and maintaining production-grade data platforms and pipelines.
  • Strong programming skills in general-purpose language (such as Python or Scala) for data processing, and SQL for data analytics.
  • Deep experience with distributed data processing frameworks, such as Apache Spark, including performance tuning and optimization.
  • Proven experience building data solutions using services on AWS (EMR, Lambda, s3, etc).
  • Strong understanding of data modeling and data warehousing concepts, including partitioning, schema design for large-scale datasets.
  • Experience operating and supporting production pipelines, including monitoring, alerting, incident response, and improving reliability over time.
  • Solid foundation in software engineering practices, including version control, CI/CD, testing strategies, and code review.
  • Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.

Nice To Haves

  • Experience with streaming or near-real-time data processing (Kafka, Kinesis, etc).
  • Hands-on experience with data orchestration tools (Airflow, Step Functions, etc).
  • Familiarity with modern data platform patterns such as Data Lakehouse, Data Mesh, and large-scale data sharing across teams.
  • Experience with prompt engineering using modern GenAI, Large Language Models (LLM).
  • Experience mentoring other engineers and contributing to engineering-wide standards, best practices.

Responsibilities

  • Design and build batch and streaming data pipelines to support automated data ingestion, ML feature engineering and analytics across multiple product domains.
  • Own end-to-end delivery of complex, ambiguous data initiatives, including architecture, implementation, testing, deployment, monitoring, and documentation.
  • Develop and evolve the data platform to support large-scale data processing using modern cloud-native technologies.
  • Automate data operations (validation, quality checks, alerting, backfills, and recovery workflows) to reduce manual effort and improve consistency.
  • Optimize cost, performance, and reliability of data workloads.
  • Partner closely with cross-functional teams (Data Science, Product, Engineering) to understand requirements, translate them into technical solutions.
  • Evaluate and adopt new technologies (new processing engines, storage formats, orchestration tools, GenAI-assisted ingestion) to keep the platform modern and efficient.

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

No Education Listed

Number of Employees

101-250 employees

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