Description

You will design and build scalable enterprise cloud data warehouse solutions and data pipelines.

This role is hybrid.

Responsibilities

• Design and develop enterprise cloud data warehouse solutions and dimensional models.
• Build scalable batch and near real-time data pipelines using Python, PySpark, and Scala.
• Develop reusable ingestion frameworks for trading, risk, treasury, and finance systems.
• Implement data quality, governance, metadata management, and lineage frameworks.
• Optimize warehouse performance, compute utilization, and storage costs.

Required Skills

• 6–10+ years of Data Engineering experience with a Bachelor's degree.
• Advanced SQL and strong hands-on expertise in Python, PySpark, or Scala.
• Experience with ETL/ELT development, data modeling, and data warehousing.
• Proficiency with Snowflake or Databricks on AWS and/or Azure Cloud.
• Experience building enterprise data pipelines using Airflow, dbt, or Kafka.
• Familiarity with Informatica or Talend for data integration.
• DevOps and automation skills: Git, CI/CD, Terraform, Docker, and Kubernetes.
• Strong understanding of data governance, metadata management, and data reconciliation.

Preferred Skills

• Banking, Financial Services, or Capital Markets experience.
• Experience with streaming platforms (Kafka), Airflow/Control-M, and Jenkins/GitHub Actions.

Key Skills

Education

Bachelor's degree