Job Function
Financial Services
Description
Responsibilities- Build and optimize scalable data pipelines and data products.
- Develop reliable datasets for analytics, reporting, and AI applications.
- Establish data engineering standards, frameworks, and best practices.
- Improve data quality, monitoring, testing, and platform observability.
- Integrate and reconcile complex datasets from multiple sources.
- Partner with business stakeholders and technical teams to deliver impactful solutions.
- Drive automation and operational excellence across the data platform.
- Mentor engineers and contribute to technical leadership within the team.
Qualifications
- 6+ years of data engineering experience in production environments.
- Advanced Python and SQL skills.
- Strong experience with Databricks, Snowflake, or similar cloud data platforms.
- Hands-on experience with Spark/PySpark and large-scale data processing.
- Deep understanding of data modeling, ETL/ELT, and data warehousing concepts.
- Experience building data quality, validation, and monitoring solutions.
- Comfortable working with complex, imperfect datasets and solving data integrity challenges.
- Strong communication skills and ability to operate independently.
- Bachelor's degree in a technical or quantitative field.
Preferred
- Azure cloud experience.
- Background working with financial, healthcare, life sciences, or alternative data.
- Experience with CI/CD, Terraform, and modern data engineering tooling.
- Exposure to AI/ML platforms and data products.
- Previous leadership or mentoring experience.
Job ID: 85916124
