Job Description

Required Qualifications Bachelors degree in Computer Science, Engineering, Information Systems, or a related field; equivalent practical experience may be considered. 5 years of experience developing and supporting data integration, ETLELT, or data engineering solutions. Demonstrated experience processing large data volumes in distributed or cloudbased environments. Strong proficiency in SQL and at least one programming language such as Python, Java, Scala, or Spark SQL. Experience with orchestration and workflow tools such as Apache Airflow, Azure Data Factory, AWS Step Functions. Working knowledge of relational and nonrelational databases, data warehouses, and data lake architectures. Experience designing resilient pipelines with logging, monitoring, retry logic, idempotency, and failure recovery. Strong analytical, troubleshooting, communication, and collaboration skills. Preferred Qualifications Experience with cloud data platform AWS. Experience with AWS services to include Lambda and KAFKA Knowledge of data modeling, metadata management, data governance, and master data management practices. Experience with containerization and deployment technologies, CICD pipelines, and infrastructure as code. Experience working in regulated, financial services, healthcare, or other highly controlled environments. Technical Environment The successful candidate will work with a modern data engineering ecosystem that may include cloud storage, data lakes, data warehouses, distributed compute platforms, streaming systems, APIs, orchestration tools, source control, automated testing, and observability platforms.