About the Project
The customer is a global investment management firm that provides tailored investment solutions to institutional and private clients. It combines financial expertise with long-term investment strategies, adapts to changing market conditions, and focuses on innovation, responsible investing, and operational excellence. The project automates revenue reconciliation within a large-scale data platform, improving payment reconciliation accuracy, transparency, and operational efficiency.
Responsibilities
•Gather and clarify requirements from marketing analysts and BI, translating them into changes to attribution logic, sources, and data marts
•Lead the migration of the attribution pipeline, including dbt models, Airflow DAGs, and sources, to the core DWH platform; run both pipelines in parallel and reconcile results before switching over
•Build and optimize incremental data marts in BigQuery using dbt, SQL, and Airflow, including recalculations and backfills
•Design and implement data quality checks and investigate discrepancies against product and source data
•Analyze external inputs, including AppsFlyer, ad network cost feeds, Google Sheets dictionaries, and upstream marts, to ensure reliable data flow from source to consumption
•Participate in testing, data validation, and release processes, including repointing downstream consumers
•Maintain technical documentation for the domain and share knowledge across the team
Requirements
•At least 3 years of experience as an Analytics Engineer, DWH Engineer, or Data Analyst working with DWH
•Hands-on experience with data warehouses
•Strong understanding of DWH architecture and data layers, including ODS and Data Marts
•Understanding of incremental loads, historical data handling, and deduplication
•Expert SQL skills
•Experience designing and optimizing data marts
•Experience with BigQuery or a similar columnar database
•Experience with dbt on large incremental projects
•Experience migrating pipelines between platforms and validating data parity
•Experience with Airflow or a similar orchestration tool
•Knowledge of Python for data processing and ETL tasks
•Ability to work with stakeholders and translate business needs into data requirements
•English at Intermediate+ level or above
Nice to Have
•Mobile and marketing attribution data experience with AppsFlyer, Adjust, or Branch, including ad network cost data, SKAN, and ATT
•Familiarity with ad fraud detection and analytics, particularly AppsFlyer Protect360
•GCP experience, including Cloud Storage and Dataform
•Experience with analytics and BI tools such as Lightdash, Looker, and Tableau
Conditions
•Up to an additional 1,000 EUR per month, depending on expertise level, included in the annual bonus for participation in company activities
•Professional, financial, and career growth opportunities; mentoring and adaptation systems for each new employee
•Access to the corporate training portal and company knowledge base
•Corporate events and amenities, including parties, pizza days, PlayStation, fruit, coffee, snacks, and movies
•Certification compensation, including AWS and PMP
•Referral program
•Private health insurance and sports compensation, depending on the type of employment
