• Data Engineer

    Robert Half Technology (Los Angeles, CA)


    Description

    Our team is seeking an experienced Data Engineer to help architect, build, and optimize data infrastructure supporting enterprise decision making and advanced analytics. This position is ideal for hands-on professionals who excel in SQL, Python, and have proven expertise across enterprise cloud platforms, databases, and modern data engineering practices.

    Key Responsibilities:

    + Design, develop, and maintain scalable data pipelines that ingest, process, and transform structured and unstructured data.

    + Write advanced SQL queries—including complex joins, aggregations, window functions, and CTEs—to support ETL, data analysis, and migration projects.

    + Develop, optimize, and productionize Python scripts for data movement and validation using vanilla Python; familiarity with PySpark is a plus.

    + Collaborate across teams to deliver robust APIs and services for data integration with frontend (React, Angular, Vue) and backend (Node.js, Express) frameworks.

    + Architect and maintain data models and schemas, ensuring alignment with business requirements and efficient data retrieval.

    + Manage production-level SQL (e.g., SQL Server) and NoSQL (e.g., MongoDB) databases; ensure data quality through continuous monitoring and rigorous testing.

    + Deploy and manage automated ETL pipelines and schema migrations using Azure Data Factory, Microsoft Fabric, or comparable technologies.

    + Continuously improve performance through query optimization and efficient use of data structures (lists, dictionaries, sets) in Python.

    + Implement agile methodologies, continuous delivery, and DevOps best practices for reliable and scalable data infrastructure.

    + Enforce rigorous data quality management and automated testing strategies to ensure accuracy and reliability of data assets.

    Requirements

    + 5+ years data engineering experience.

    + Advanced proficiency in SQL (SELECT statements, joins, aggregations, subqueries, window functions, CTEs, DML statements, schema design, and query optimization).

    + Strong experience in Python (native/vanilla), effectively leveraging core data structures for data manipulation; PySpark experience is a plus.

    + Demonstrated ability to build production-level scripts/services in JavaScript/TypeScript and Python; hands-on with frontend (React, Angular, Vue) and backend (Node.js, Express) frameworks.

    + Proven expertise with Azure Data Factory, Microsoft Fabric, or other enterprise-grade data platforms.

    + Extensive work with both SQL and NoSQL databases (SQL Server, MongoDB), including schema modeling, complex querying, and troubleshooting data migrations.

    + Comfort maintaining projects in Git/GitHub; experience in automated deployments, CI/CD, and schema migrations.

    + Solid foundation in agile development, continuous delivery, and designing/maintaining RESTful APIs (security, testing, performance, JSON).

    + Deep understanding of data quality, test strategy development, and test automation in data solutions.

     

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