An exciting opportunity to join our client's team at a leading media and entertainment company in Central and Eastern Europe . We are looking for a Senior Data Engineer to join this organization.

Responsibilities

• Role summary
• We are rebuilding the foundations of our data platform
• moving from a fragmented setup toward a cloud-centered lakehouse, standardizing transformations with dbt, orchestrating with Airflow and preparing for a major possible change of event flows and identity modeling. You will be the senior hands-on engineer who turns this into a reliable, documented, testable data foundation that powers our tools and analytical/predictive systems.
• Context you’ll step into
• Current data landscape includes multiple layers, historically involving tools like Snowflake and a BigQuery reporting layer; target is to unify layers and governance around cloud, standardize ELT in dbt, and orchestrate reliably.
• We must also integrate more product telemetry (carousel/promo exposure, etc.) and support CRM activation pipelines.
• How you’ll work
• You will work in a tight triangle:
• Senior Data Engineer (this role): owns data modeling, dbt transformations, BigQuery performance, pipeline correctness, and analytics “source of truth”.
• AI Infrastructure & DevOps Engineer: owns cloud infrastructure, CI/CD patterns, deployment mechanics, security, and platform reliability.
• Data Scientists / Analytics users: define business logic needs, validate outputs, and consume marts/features.
• Expectation: very close synchronization with the AI Infra/DevOps engineer on the end-to-end flow (environments, scheduling, monitoring, deployment workflow). You won’t be the CI/CD owner, but you’ll be the person who ensures the data layer is correct, scalable, and production-grade, and that it plugs cleanly into the existing engineering standards.
• What you’ll do:

A) Build the Cloud lakehouse

• Implement a clear layered model (00 raw/landing, staging, intermediate, marts/30).
• Co-build with AI Infra engineer, scalable BigQuery datasets
• partitioning/clustering strategies, cost/performance optimization.
• Define canonical business tables for our business needs

B) Standardize transformations with dbt

• Implement dbt project structure, naming conventions, documentation, tests.
• Build incremental models, snapshot patterns (SCD), and clear semantic definitions.
• Enforce quality gates
• schema tests, uniqueness, freshness, anomaly checks.

C) Orchestration & reliability (Airflow / Cloud Composer)

• Productionize DAGs for ingestion + dbt runs + monitoring.
• Add observability
• SLAs, retries, alerting, backfills, lineage.
• Ensure reliable refresh cadence for our tools and ML flows.

D) Ingestion & integration (including migration readiness)

• Build/own ingestion patterns from source systems into BigQuery
• Prepare for the new platform migration
• adapt pipelines to new event schemas and identity model; maintain continuity for analytics and ML.

Requirements

Certifications

In addition to the salary, the company offers the following benefits

• Medical Plan
• Access to premium healthcare services with options to include family members.
• Hospitalization Insurance: Coverage through Groupama for peace of mind during unexpected medical events.
• Employee Assistance Program (EAP): Confidential support for personal and family challenges.
• On-site Massage: Relax and recharge at work.
• Meal Vouchers
• Holiday Vouchers
• Volunteering Days: 4 paid days to give back to the community.

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