Location: St. Louis, MO

Title: Data Engineer

Experience: 10 Years (Software/Data Engineering)

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Job Description

Core Responsibilities

• Drive adoption and implementation of tools and platforms that support both internal and external customers.

• Serve as a key contributor across the full data/software/platform development lifecycle: design, development, documentation, testing, deployment, and support.

• Operate efficiently within highly secure environments adhering to PII and PCI-DSS standards.

• Support architects and engineers in designing and building scalable, secure, and agile data applications and platforms.

• Design, develop, and optimize batch and real-time data pipelines using Medallion Architecture, preferably on Snowflake or Databricks.

• Build modular, test-driven data transformation workflows using dbt, following strict TDD practices.

• Implement CI/CD pipelines via GitLab and Jenkins for automated testing, deployment, and monitoring.

• Embed DataOps principles across all phases of the pipeline lifecycle testing, monitoring, versioning, collaboration, and automation.

• Create scalable, reusable data models to support analytics and reporting, including Power BI dashboards.

• Develop, optimize, and support real-time streaming pipelines using technologies such as Kafka and Spark Structured Streaming.

• Establish data observability frameworks for monitoring data quality, freshness, lineage, and anomaly detection.

• Lead deployments, migrations, and upgrades for data platforms ensuring minimal downtime and strong mitigation planning.

• Collaborate with cross-functional stakeholders to translate requirements into reliable, high-impact data solutions.

• Maintain comprehensive documentation covering pipeline architecture, processes, standards, and operating procedures.

• Troubleshoot complex data and system issues using advanced analytical and problem-solving skills.

• Communicate clearly and effectively with both technical and non-technical stakeholders.

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Required Qualifications

• Bachelor s degree in Computer Science, Engineering, or related technical discipline.

• 15 years of proven experience in software development, data engineering, or platform engineering.

• Deep hands-on expertise with Databricks, Python, PySpark, and Spark SQL.

• Strong experience building high-performance transformations involving joins, window functions, aggregations, partitioning, and caching strategies.

• Skilled in developing and managing real-time streaming pipelines.

• Experience with Delta Live Tables (DLT) and Databricks Workflows; knowledge of Lakeflow Declarative Pipelines is a plus.

• Strong DevOps background including:

  • Databricks Asset Bundles (DABs)

  • Git/GitHub/Bitbucket

  • Jenkins automation

• Proven experience with dbt for modular, testable, and scalable transformation workflows.

• Solid understanding of cloud database ecosystems (AWS, Azure, or Google Cloud Platform).

• Expertise in designing scalable data models and dashboards using Power BI.

• Advanced SQL development and query optimization skills.

• Demonstrated capability in building and managing data observability frameworks.

• Strong track record in planning and executing large-scale deployments, upgrades, and migrations with minimal operational impact.

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