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Data Engineer
Company | Voya Financial |
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Location | New York, NY, USA |
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Salary | $113250 – $141560 |
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Type | Full-Time |
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Degrees | Bachelor’s |
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Experience Level | Senior |
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Requirements
- 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.
Responsibilities
- 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.
Preferred Qualifications
- 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.