A growing, globally oriented firm is looking for a skilled Data Engineer to join its Boston-based engineering group. This role offers the opportunity to make a meaningful contribution from day one within a collaborative, high-growth environment. The team values individuals who are proactive, adaptable, and comfortable operating in a fast-moving, evolving setting alongside a small, focused group of engineers.
Core Responsibilities
Develop and maintain robust, scalable data pipelines that connect both internal systems (such as portfolio and order management platforms) and third-party data providers (e.g., financial market data sources)
Work with complex datasets across multiple platforms, ensuring accuracy, reliability, and efficient structure
Partner with cross-functional teams-including data governance, AI, and application engineering-to deliver impactful, business-driven data solutions
Contribute as an active member of a small agile engineering team, participating in sprint planning, stand-ups, and other iterative development processes
Build and support data ingestion and transformation workflows using Python and relational databases such as MySQL
Design and optimize ETL processes leveraging cloud-based integration tools (e.g., Azure Data Factory or similar)
Implement and manage data models within cloud data warehouse environments such as Snowflake
Support the development of AI-enabled data features, including semantic layers and automated insights capabilities
Follow engineering best practices to produce clean, scalable, and well-tested code
Troubleshoot and resolve challenging data integration and performance issues across systems
Contribute to the evolution of a modern data platform built on top of an existing enterprise data ecosystem
Help deliver innovative data capabilities in a collaborative and fast-paced engineering culture
Additional Responsibilities
Adhere to organizational security policies and promptly escalate any risks or concerns to the appropriate teams
Ensure compliance with applicable data privacy regulations and internal data protection standards
Be flexible in supporting changing business priorities, which may occasionally require additional working hours
Candidate Profile
The ideal candidate will have a strong technical background in data engineering or a related discipline (such as Computer Science), or equivalent practical experience. Success in this role requires independence, curiosity, attention to detail, and a commitment to writing high-quality, maintainable code. Strong collaboration skills and sound problem-solving judgment are also essential.
Required Qualifications
Demonstrated experience designing and building data warehouse solutions with complex schemas
Strong understanding of data modeling techniques, including dimensional modeling (e.g., star schema)
Approximately 5+ years of professional experience in data engineering roles
Hands-on experience with Snowflake (roughly 3+ years), including advanced features such as AI capabilities or semantic modeling
Proficiency in Python (3+ years or equivalent experience)
Solid SQL and database skills, ideally with MySQL or similar systems
Experience working with APIs and integrating external data sources
Familiarity with agile development methodologies
Strong interest in solving complex technical problems through programming
Preferred Qualifications
Knowledge of software design patterns and best practices for Python-based applications
Experience with data visualization tools (e.g., Power BI or similar)
Experience using cloud-based data orchestration tools such as Azure Data Factory
Exposure to modern AI tools or frameworks (e.g., generative AI, agent-based systems)
Experience collaborating across geographically distributed or cross-functional teams