Job Requirements

JD

Data Engineer to design and manage heavy-duty data pipelines, modernize legacy data warehouses, and move on-prem tech into the cloud. Build ETL/ELT pipelines using PySpark, AWS Glue, and Oracle PL/SQL, set up data lakehouses (Medallion style), automate workflows with Step Functions, and fine-tune database performance. Leadership & Teamwork: Guide junior engineers, handle code reviews, and help lead project delivery in an Agile/Scrum setup.

Experience Needed: 8+ years focused on data engineering, data warehousing, or database optimization, preferably within banking or financial services.

Tech Stack: Deep know-how in Oracle (19c/23ai, Exadata, PL/SQL), Redshift, Python (PySpark, Pandas), AWS cloud services (S3, Glue, Step Functions, EventBridge), and CI/CD tools like Jenkins or GitHub Actions.

Nice to Haves: AWS Solutions Architect or Azure Fundamentals certifications, plus experience with Apache Iceberg, Scala, or multi-cloud environments.

Education: Bachelor's or Master's in Computer Science, Software Engineering, or a related field.

Work Experience

10-15Years

📌 Lead Data Engineer (Sydney)
🏢 Virtusa
📍 Sydney