Data Engineer

Bachelor’s Degree in Computer Science, MIS, Engineering or a directly related field.
5+ years of experience in data engineering, with a strong background in building and maintaining data pipeline and ELT processes to ingest data from external data provider.
Strong proficiency in SQL and experience with relational database design.
Strong proficiency in Python.
Experience with Snowflake and Snowpark.
Experience with AWS or Azure.
Experience with orchestration tools such as Airflow, Prefect, or Dagster.
Knowledge of Investment Management and financial data.
Excellent communication skills with the ability to collaborate effectively with cross-functional business and technology groups.
Commitment to learning or curious about new tools / technologies.

Design, develop, and maintain scalable and efficient data pipeline and ELT processes.
Parse, analyze, and understand datasets with a focus on application in business use cases.
Manage data storage solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems.
Perform data reconciliations, validations, quality checks across various data sources and systems and identify enrichment opportunities.
Develop new systems and maintain and modify existing systems as required.
Provide support in system acceptance testing and validation activities.
Analyze project requirements and accordingly provide technical and functional recommendations.
Lead junior data engineers, fostering a culture of continuous learning and improvement and providing guidance and support in their professional development.
Additional responsibilities, as required.

Experiences with LLMs and NLP.
Experience with Databricks and PySpark.
Experience with Data Test and Quality framework such as SODA, Great Expectation, dbt test.
Experience with dbt.
Experiences with Market Data and/or Alternative Data.
Experience with scheduling tools such as Tidal, Control-M, or cron.