Data Engineering Analyst - Portfolio Analytics & Reporting
StepStone Group is a global private markets specialist delivering tailored investment solutions and impactful data-driven insights. The Data Engineering Analyst will take ownership of a client-facing pipeline, ensuring timely data deliveries while building and maintaining data pipelines to support analytics and reporting.
Responsibilities
- Own daily client-facing pipeline operations: Monitor, validate, and ensure timely and accurate file deliveries to clients via automated Airflow jobs
- Troubleshoot and resolve data or delivery issues, coordinating with internal and client stakeholders as needed
- Build and maintain monitoring, alerting, and validation checks to meet SLAs, data quality standards and enhance pipeline reliability
- Support development and maintenance of end-to-end ELT processes using Airbyte, dbt, Airflow, and Snowflake, with final data output following star-schemas and snowflake-schemas
- Implement data validation and reconciliation logic to ensure completeness and integrity across systems
- Contribute to automation and DevOps practices (CI/CD, code reviews, documentation, and runbooks)
- Support other data initiatives such as master data management, data modeling, and ad-hoc analysis
Skills
- Bachelor's degree in Computer Science, Information Systems, or a related quantitative field
- 1-3 years of experience in data analysis or a junior data engineering role
- Strong SQL skills
- Scripting ability (Python or similar) for automation and troubleshooting
- Familiarity with modern data tools (Snowflake, dbt, Airflow, Airbyte) or a strong willingness to learn
- Ownership mindset, strong sense of responsibility, and attention to detail
- Solid communication skills; comfortable liaising with technical and non-technical stakeholders
- Ability to triage and solve problems under pressure
- Experience operating production pipelines (monitoring, SLAs, incident management)
- Knowledge of version control (Git), CI/CD, or infrastructure as code
- Experience working with Snowflake is preferred
- Exposure to cloud platforms (AWS, GCP, Azure)
- Experience with data testing frameworks (e.g. dbt tests, validation frameworks)
- Familiarity with finance, private markets, or investment data domains
Company Overview
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