Data Engineer

Employment Type :
Full-time

Experience :
4-7 Years

Overview:

Data Engineer with strong 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 high-quality, 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.