Job Description

Responsibilities

• Design, build, and maintain scalable data pipelines and data workflows across a modern data environment.
• Develop and optimize data solutions using Snowflake, dbt, and Airflow .
• Build and enhance data lakes and data platforms , integrating data from a variety of internal and external sources.
• Develop reliable ETL/ELT processes to support reporting, analytics, and downstream applications.
• Establish data transformation and modeling frameworks using dbt .
• Develop and manage workflow orchestration using Apache Airflow .
• Optimize Snowflake environments for performance, scalability, reliability, and cost.
• Partner with data analysts, technology teams, and business stakeholders to understand requirements and translate them into effective data solutions.
• Implement data quality, monitoring, testing, and governance practices across pipelines and data products.
• Troubleshoot data pipeline and platform issues and proactively identify opportunities for improvement.
• Contribute to the ongoing evolution of the firm's data architecture and engineering standards.
• Clearly communicate technical solutions, project status, risks, and recommendations to both technical and non-technical audiences.

Qualifications

• 5+ years of experience in data engineering, data platform engineering, or a related discipline .
• Strong hands-on experience with Snowflake .
• Experience building and maintaining data pipelines using modern ETL/ELT technologies.
• Strong experience with dbt and data transformation/modeling.
• Experience with Apache Airflow or similar workflow orchestration platforms.
• Experience designing and building data lakes, data warehouses, and/or modern cloud data platforms .
• Strong SQL skills and experience working with large, complex datasets.
• Experience with Python or another programming language commonly used in data engineering.
• Understanding of data architecture, data modeling, data quality, and data governance principles.
• Ability to work effectively in a fast-paced, collaborative environment.

Preferred Qualifications

• Experience working within financial services, private equity, investment management, banking, hedge funds, or asset management .
• Experience working with financial or investment-related datasets.
• Exposure to cloud platforms such as AWS, Azure, or GCP .
• Experience with additional modern data technologies and cloud-based data platforms.
• Experience supporting data initiatives involving analytics, AI, or machine learning.

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