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About the role
\nWe are looking for an Agile, product-oriented Senior Analytics Engineer to drive our
\nmodern data architecture. You will be the bridge between raw data and business value for
\nour digital products and online services.
\nIn this role, speed and value are key. You will adopt an MVP (Minimum Viable Product)
\nmindset to launch data products quickly, iterate fast, and provide actionable insights for our
\nMarketing and Finance teams. You will work on our cutting-edge stack—building robust
\npipelines in dbt and BigQuery, and exposing data through our next-generation semantic
\nlayer in Omni Analytics.
\n
\nWhat you will do
\n● Modern Data Modeling: Design, build, and maintain scalable dbt models in
\nBigQuery. Transform raw data into clean, tested, and documented data marts ready
\nfor analysis.
\n● MVP Delivery: Adopt a fast-paced, product-oriented mindset. Launch Minimum
\nViable Products for data reporting to give product and business stakeholders quick
\nanswers, then iterate based on feedback.
\n● Semantic Layer Ownership: Implement and govern the business logic in Omni
\nAnalytics (or similar modern BI tools), ensuring metrics are defined once and trusted
\nby everyone.
\n● Cross-Functional Analytics: Collaborate closely with Marketing and Finance
\ndepartments to understand our digital platform metrics (CAC, LTV, ROI, conversion
\nfunnels, retention, and MAUs) and translate them into technical solutions.
\n● Quality & CI/CD: Apply software engineering best practices to data: version control
\n(Git), automated testing, and CI/CD workflows for data pipelines.
\n
\nRequirements
\n● Experience: 6+ years in a Data Engineering, Analytics Engineering, or advanced BI
\nrole.
\n● Modern Data Stack (Essential): Extensive experience with dbt and cloud data
\nwarehouses (preferably BigQuery, though Snowflake/Redshift is valid).
\n● BI & Semantic Layers: Experience with Omni Analytics is highly desired.
\nAlternatively, strong experience in Looker (LookML), Power BI, or Tableau, with a
\nclear understanding of semantic layers and governed metrics.
\n● Domain Knowledge: Strong understanding of digital products, online services, and
\nhigh-traffic platform dynamics. Exposure to Marketing and Finance data is highly
\ndesirable.
\n● Technical Skills: Advanced SQL optimization, data modeling (star schema, OBT),
\nand Git workflow.
\n● Mindset: MVP-oriented, proactive, and capable of finding innovative solutions to
\nchallenging problems.
\n
\nTools you will work with
\nBigQuery · dbt · Omni Analytics · SQL · Git · Digital product analytics platforms

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