Senior Data Solutions Engineer

    Highlights

    This role is designed for an experienced analytics professional who operates comfortably across analytics and data engineering, serves as a thought partner to the business, and takes ownership of delivering trusted, scalable, analytics-ready data products. You will work closely with business stakeholders, analytics partners, and data engineering teams to ensure data is reliable, well-documented, and ready to support advanced analytics and AI use cases.

    Numbers & Facts

    LocationNY

    Description

    We are seeking a Senior Data Solutions Engineer to join our growing Data Products & Platforms team. This role is designed for an experienced analytics professional who operates comfortably across analytics and data engineering, serves as a thought partner to the business, and takes ownership of delivering trusted, scalable, analytics-ready data products.

    As a senior member of the team, you will play a key role in shaping the analytics data layer, defining standardized metrics and datasets, and enabling high-quality reporting and self-service analytics across the organization. You will work closely with business stakeholders, analytics partners, and data engineering teams to ensure data is reliable, well-documented, and ready to support advanced analytics and AI use cases.

    What You'll Do

    • Design, build, and own analytics-ready datasets in Snowflake using curated ELT pipelines (e.g., Coalesce.io)
    • Develop and maintain Snowflake semantic views to standardize business logic, KPIs, and metric definitions across teams
    • Act as a trusted partner to business stakeholders by translating analytical needs into scalable, reusable data solutions
    • Enable and support self-service analytics across BI tools such as Sigma and Power BI
    • Establish and maintain clear documentation for datasets, metrics, and analytical models
    • Proactively monitor, validate, and improve data quality, performance, and reliability
    • Collaborate closely with data engineering and platform teams to evolve and optimize the analytics data layer
    • Support AI and advanced analytics initiatives by delivering well-structured, high-quality datasets suitable for forecasting, machine learning, and generative AI
    • Contribute senior-level guidance on analytics engineering best practices, data modeling standards, and dataset design

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