Senior Data Engineer

Selby Jennings Ltd

  • Boston, MA
  • 7 days ago

    Highlights

    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). Contribute as an active member of a small agile engineering team, participating in sprint planning, stand-ups, and other iterative development processes.

    Numbers & Facts

    LocationBoston, MA

    Description

    Role Overview

    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

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