Data Engineer with solid DevOps and analytical skills to design, build, and maintain scalable data pipelines for financial data. This role supports Engineering, Operations and analytics teams by delivering highquality, reliable datasets and automated workflows.
Key Responsibilities
- Build and maintain ETL/ELT pipelines for financial datasets.
- Develop data pipelines and optimized structures for analytics and reporting.
- infrastructure-as-code, and pipeline monitoring (DevOps/DataOps).
- Ensure data quality, lineage, and governance across platforms.
- Collaborate with Engineering, Operations and Analytics teams to support reporting and insights.
- Optimize pipeline performance, reliability, and cloud resource usage for cost optimization.
Required Qualifications
- Masters degree in computer science, Data Engineering, Information Systems, or related field.
- 3–5 years of hands-on experience in data engineering.
- Strong SQL and Python; experience with Spark or equivalent.
- Experience with cloud data platforms (Spanner, BigQuery, Redshift, or similar).
- Proficiency with DevOps tools (Git, CI/CD pipelines, Terraform/IaC).
- Experience with orchestration tools (Airflow, Pentaho).
- Understanding of financial datasets and domain concepts.
- Knowledge of data quality/observability tools.
📌 Data Engineer with DevOps (Hyderabad)
🏢 Softility Tech
📍 Hyderabad
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