Associate Data Engineer
Permanent - Full TimeJob Overview
Location - Pittsburgh, Boston, Toronto or Montreal
Why Confluence?
At Confluence, we’ve always been driven by a commitment to innovation, precision, and partnership in the investment data space. Our global footprint now spans multiple countries, giving our employees the opportunity to get exposure to other countries and cultures. And it stands to reason that none of this would have been possible without the hundreds of hard-working employees who work at Confluence.
More about the role & team
We’re looking for an Associate Data Engineer to join our growing data platform team. In this role, you’ll work closely with experienced engineers and analysts to build reliable data pipelines and help shape how data flows across the organization.
This is a hands-on, development-focused opportunity where you’ll be writing code daily, solving real data challenges, and contributing to scalable data solutions—not just maintaining systems. It’s a great role for someone early in their career who is eager to learn, collaborate, and develop their technical skills in a modern data environment.
Why Should You Apply?
- Work in a collaborative team where learning and mentoring are part of the culture
- Gain hands-on experience with modern data tools and technologies
- Build a solid foundation for a long-term career in data engineering
- Contribute to meaningful projects that support real business decisions
What skills and experience do I need to succeed?
What We’re Looking For
- Some hands-on experience with Python for data processing or automation
- Good working knowledge of SQL, including working with larger datasets
- Exposure to ETL pipelines or data workflows (academic, internship, or professional experience)
- Understanding of data modelling or transformation concepts
- Comfortable working in a collaborative, code-first environment
Nice to Have
- Experience with Snowflake
- Exposure to cloud platforms like AWS, Azure, or GCP
- Familiarity with orchestration tools (e.g., Airflow)
- Interest or exposure to financial data environments