Data Engineer

General Purpose of Job Data Engineer role is responsible for design, build, test, deployment, and support of enterprise data pipelines (CI/CD), lakehouse tables, transformation frameworks, change data capture (CDC), metadata controls, data quality processes, and governed data products. This role is responsible for implementing reliable data movement and transformation patterns across modern cloud data platforms, including Microsoft Fabric, Azure data services, Databricks, Snowflake, or comparable lakehouse and warehouse technologies. The Data Engineer should be able to transform data using PySpark, Spark SQL, Python, SQL, and deep understanding of related frameworks, and deep understanding of related frameworks The role requires practical understanding of medallion architecture, Delta / open table formats, data catalogs, data products, dimensional modeling, metadata management, master data management, governance, security, data mesh, domain-driven design, DevOps, observability, and operational support. The position supports the full lifecycle of data products: ingestion, raw/bronze landing, source registration, technical staging, silver conformance, gold semantic publishing, metadata capture, quality validation, promotion, monitoring, and support. The engineer partners with analysts, architects, business SMEs, data stewards, security teams, and platform administrators to deliver data products that are trusted, documented, secure, reusable, and performant. Minimum Required Qualifications and Competencies The following includes the minimum job requirements and essential duties for this position. Reasonable accommodation may be made to enable qualified individuals with disabilities to perform the essential functions. Some job requirements may exclude individuals that cannot be reasonably accommodated or who pose a direct threat or significant risk to the health and safety of themselves or other employees. Education Minimum: Four (4) year bachelor's degree from an accredited institution in computer science, information systems, data engineering, software engineering, mathematics, statistics, engineering, or a related technical field. Preferred: Certifications or formal training in Microsoft Fabric, Azure Data Engineer, Databricks, Spark, Snowflake, data governance, DevOps, data modeling, or cloud architecture. Job-related experience may be substituted for the required education on a year-for-year basis. Experience Minimum: Four (4) years of progressively responsible experience in data engineering, ETL/ELT development, analytics engineering, database development, BI engineering, software development, cloud data platform engineering, or related technical work. Preferred: Experience designing and operating lakehouse or warehouse platforms, medallion data flows, Spark/PySpark workloads, Data Factory or pipeline orchestration, metadata-driven frameworks, dimensional models, master data, and governed semantic-ready marts. Preferred: Experience with Microsoft Fabric, Azure Data Lake Storage, OneLake, Delta Lake, Synapse, Databricks, Snowflake, Power BI semantic models, Git-based DevOps, and enterprise operational data. Other Requirements Ability to operate a variety of office equipment, including a personal computer, printers, copy machines, telephone. Ability to work irregular hours in evenings and on weekends for assignment completion and flexibility to change scheduling and report to work on short notice during emergency situations. Normal work hours shall be eight (8) hours between 7:00 am and 5:00 pm, Monday through Friday. Successful completion of pre-employment background check, physical and drug screen. #J-18808-Ljbffr