Cloud)

TSG Risk Management•New York City, NY

1d•Hybrid

About The Position

We are seeking a well-rounded Data Engineer to design, build, and support scalable data pipelines, analytics solutions, and reporting tools. This role sits at the intersection of data engineering, analytics, and stakeholder collaboration, and will play a key role in delivering high-quality, data-driven insights across the organization. The ideal candidate is hands-on with Python, SQL, and ETL development, while also being comfortable building Power BI dashboards and partnering with cross-functional teams in an Agile environment.

Requirements

4–6+ years of experience in data engineering or related field
Strong experience with Python and SQL
Hands-on experience building and maintaining ETL/data pipelines
Experience with data modeling and working with structured datasets
Experience with Power BI (dashboard development and reporting)
Familiarity with cloud platforms (AWS, Azure, or GCP)
Experience working in Agile environments with cross-functional teams
Strong problem-solving skills and attention to detail
Excellent communication skills with the ability to work with both technical and non-technical stakeholders

Nice To Haves

Experience with data automation and metric standardization
Exposure to infrastructure deployments or DevOps practices
Experience with Confluence or similar documentation tools
Prior experience supporting enterprise reporting or analytics initiatives

Responsibilities

Design, develop, and maintain secure and scalable data pipelines and ETL processes
Build and optimize data models to support analytics and reporting use cases
Develop Power BI dashboards and reports to deliver actionable insights
Collaborate with cross-functional stakeholders to gather requirements and translate them into technical solutions
Participate in Agile ceremonies and project meetings, ensuring alignment on deliverables, timelines, and quality standards
Implement data quality controls and ensure accuracy, consistency, and reliability of data outputs
Develop and maintain Python scripts for data extraction, transformation, and automation
Support metric development and reporting automation initiatives
Contribute to infrastructure-related activities, including deployments and environment support
Create and maintain technical documentation (e.g., Confluence)
Provide regular updates on progress, risks, and dependencies to stakeholders