Data Engineer
FitMe is a fitness app created for people who want to stay active without long, repetitive workouts. It offers short, easy-to-follow routines that can be done at home with no equipment. FitMe is perfect for busy people who want to maintain their health, boost energy levels, and feel good every day — without going to the gym or spending hours on exercise.
Requirements:
- 1-2 years of commercial experience in data engineering / analytics engineering / BI development.
- Experience with data warehouse, data lake and data lakehouse concepts.
- Proven experience in designing, implementing and supporting ETL/ELT pipelines.
- Experience with AWS, Amazon Redshift, Apache Airflow.
- Advanced SQL, hands-on experience in designing production-level Python code.
- Willingness to deal with business logic (subscription, monetization, attribution) — with team support.
Would be a plus:
- Experience with Infrastructure as Code (Terraform).
- Experience with dbt, Apache Spark, Apache Iceberg
- Experience with UA-attribution stack (AppsFlyer, AppMetrica, Adjust, SKAN, GA4) and UA cost APIs (Meta, Google Ads, TikTok, AppLovin).
Responsibilities:
- Stakeholder support: ad-hoc validation of figures, investigation of discrepancies between dashboards, ensuring availability of the BI platform.
- Development and support of ETL/ELT pipelines for analytical reports (cohort revenue, LTV, retention, KPI by creatives, post-purchase analytics).
- Support for attribution models (Web↔Mobile mapping, multi-locale cost-cohort resolve, last-click vs raw events).
- Integrations with external sources: Meta Marketing API, AppsFlyer, AppMetrica, Stripe, Tableau Server (TSC), Birch.
- Data quality assurance: schema/freshness/volume checks, broken-snapshot detection, anti-bot-traffic filtering.
- Performance optimization of queries and procedures in Redshift.
- Collaboration with BI Team, Product / UA / Billing analysts.
