Data Engineer

Skills & Qualifications: • 4+ years of Data Engineering experience • Advanced SQL; experience with relational and NoSQL databases • Strong experience with Snowflake, Hadoop, Spark, PySpark, Databricks, Azure • Proficiency in Python for data engineering • Familiarity with orchestration tools and workflow management systems Responsibilities: • Design, build, and maintain scalable data pipelines using Snowflake, Hadoop, Spark, PySpark, Azure • Implement data architectures and optimize workflows for large financial datasets • Write high-quality, maintainable Python and SQL code following best practices • Integrate data governance, metadata management, and lineage tracking into solution

The Data Engineer will design, build, and maintain scalable data pipelines using various technologies. They will also implement data architectures and optimize workflows for large financial datasets.

Candidates should have over 4 years of Data Engineering experience and strong proficiency in SQL and Python. Familiarity with tools like Snowflake, Hadoop, and Azure is also required.

Identified from the job description. Confirm important requirements above.

• Data Engineering
• SQL
• Relational Databases
• NoSQL
• Snowflake
• Hadoop
• Spark
• PySpark
• Databricks
• Azure
• Python
• Orchestration Tools
• Workflow Management Systems

Minimum experience

5+ years

Apply by

Aug 12, 2026