Data Engineer
persistent
Job Description
- Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and Apache Spark.
- Build high-performance data ingestion, transformation, and processing frameworks for enterprise data platforms.
- Optimize Oracle databases, SQL queries, Spark jobs, and large-scale data processing workloads.
- Develop and support real-time and batch data integration solutions using Oracle GoldenGate, CDC, Kafka, and related technologies.
- Implement data migration and modernization strategies across legacy and cloud-based platforms.
- Design and maintain robust data models, data warehouses, and analytical datasets.
- Monitor, troubleshoot, and tune data pipelines to ensure performance, reliability, and scalability.
- Implement automation, monitoring, and operational best practices for data platforms.
- Collaborate with business analysts, solution architects, and stakeholders to translate business requirements into technical solutions.
- Ensure data quality, governance, security, and compliance across enterprise data environments.
- Participate in code reviews and contribute to engineering standards and best practices.
- Provide technical leadership and mentorship to junior engineers and team members.
- Support cloud-based data engineering initiatives and enterprise modernization programs.