Data Engineer

Role Overview This hybrid data engineering position involves designing, developing, and supporting Databricks-based data pipelines, medallion-layer data products, and enterprise integrations to enable analytics, reporting, and AI applications. Key Responsibilities Build and maintain scalable ETL/ELT workflows using Databricks, Python, Spark, and SQL. Create and support Bronze, Silver, and Gold data products aligned with business needs. Design data transformations, standardization, cleansing, and enrichment for curated data assets. Partner with cross-functional teams to translate business requirements into technical solutions. Implement data quality, validation, and governance practices to ensure reliable, discoverable data. Support data integrations, modernize legacy systems, and improve pipeline performance and stability. Use GitHub for version control, collaboration, and code promotion. Ensure secure data delivery with access controls and compliance with governance policies. Contribute to team standards, best practices, and operational support. Qualifications & Skills Bachelor’s in Computer Science, Data Engineering, or related field, or equivalent experience. 5+ years of experience in data engineering, ETL development, or data integration. Proficient with Databricks, SQL, Python, Spark, and DataStage. Experience designing data models, implementing data quality, and supporting enterprise data solutions. Strong collaboration, problem-solving, communication, and ownership skills. This role offers competitive compensation, benefits, and opportunities for growth, with an emphasis on inclusive and secure work environment. #J-18808-Ljbffr LS Solutions