We're working with a client who is looking for innovation within their product team. My client is looking for a Senior Analytics Engineer who will play a pivotal role in scaling and optimizing the Product Operations (Prod Ops). This role is responsible for building and maintaining high-value data assets, defining and implementing analytics development strategies, and ensuring consistent operational excellence within a remote, global environment.
THE ROLE AND RESPONSIBILITIES
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Partner with technical and non-technical stakeholders to bridge the gap between business challenges and technical solutions.
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Own and maintain core Product Operations data assets that serve as the Source of Truth for critical business questions.
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Develop scalable data models to facilitate efficient and high-performance analysis of HubSpot's products and operations.
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Curate, organize, and document data and reporting environments across Looker, dbt, and Amplitude.
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Collaborate with Business Intelligence (BI) and Data Engineering teams to enhance data accessibility and infrastructure.
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Define and promote best practices for SQL query optimization, data modeling, and analytics development within Snowflake SQL, dbt, LookML, and Git.
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Establish team-wide coding standards, documentation processes, and development best practices, including code reviews and testing frameworks.
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Lead requirement gathering with stakeholders and guide projects through their entire lifecycle, ensuring clear roadmaps and alignment across teams.
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Deep understanding of analysts' workflows involving both structured and unstructured datasets.
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Exceptional ability to document technical designs, ensuring clarity and usability across teams.
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3+ years of hands-on experience with advanced SQL, cloud data warehouses (e.g., Snowflake, Redshift, BigQuery), and relational databases.
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Proficiency in GitHub Enterprise for code management, peer reviews, version control, and conflict resolution.
YOUR EXPERIENCE AND QUALIFICATIONS
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Proven experience leading the technical execution of high-complexity analytics projects using advanced SQL techniques (e.g., CTEs, nested queries).
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Strong understanding of complex datasets, software development lifecycle (SDLC), and best practices in data engineering.
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Experience building and optimizing data pipelines, architectures, and entity relationships using tools like Lucidchart.
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Familiarity with multi-step ETL/ELT processes, job scheduling systems, and the ability to reverse-engineer/refactor existing technical projects.
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Conceptual knowledge of Looker (LookML, Looks, Dashboards) or other BI tools like Tableau, Qlik, or Power BI.
Please click on the link and apply to the role!