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Описание: |
We are looking for a highly skilled Data / Analytics Engineer to take ownership of our analytics layer across a modern DTC and subscription-based business.
This role sits at the intersection of data engineering, analytics, and business decision-making. You will be responsible for ensuring data accuracy, defining key metrics, and translating complex datasets into actionable insights used across product, marketing, and leadership.
Key Responsibilities
* Design, build, and maintain scalable data models across multiple sources (Shopify, Stripe, App Store, Amazon, etc.)
* Develop and optimize SQL queries (CTEs, window functions, multi-source joins, deduplication)
* Build and maintain dashboards (Grafana or similar) for real-time and operational monitoring
* Define and standardize key business metrics (LTV, cohorts, churn, ARPU, refill rates)
* Ensure data consistency across systems, including handling returns, fulfillment lag, and edge cases
* Work with ELT pipelines (e.g. Fivetran) and understand data ingestion and transformation flows
* Collaborate with product, marketing, and leadership teams to translate data into decisions
* Support investor/board-level reporting and be able to clearly explain and defend metric definitions
Requirements
* Strong SQL skills (advanced queries, performance optimization)
* Experience with data warehouses (Redshift, Snowflake, BigQuery, or similar)
* Experience building dashboards (Grafana, Tableau, Looker, or similar)
* Familiarity with Shopify, subscription models (Recharge), and eCommerce data structures
* Solid understanding of DTC metrics (LTV, retention, churn, cohort analysis)
* Experience working with ELT tools (Fivetran or similar)
* Strong analytical thinking and ability to work with imperfect data
* Ability to communicate insights clearly to both technical and non-technical stakeholders
Nice to Have
* Experience with subscription businesses or recurring revenue models
* Background in product analytics or growth analytics
* Experience with event tracking tools (Segment or similar)
* Experience with Python or data transformation frameworks (dbt, etc.)
What We’re Looking For
We are not just looking for someone who can build dashboards — we are looking for someone who can own the metric layer.
You should be comfortable answering questions like:
* How should LTV be defined for this business?
* What is the correct way to count a “customer”?
* How do returns and fulfillment delays affect revenue reporting?
This role requires both technical depth and strong business judgment.
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