Data Engineer

About the role

As a Data Engineer you will model marketing data in BigQuery, turn it into actionable dashboards, and automate data pipelines using Python. You will work closely with internal teams and clients to ensure reliable, fast, and cost‑effective reporting.

Key responsibilities

• Design, build and maintain Data Studio dashboards that answer real marketing questions and blend multiple data sources.
• Model marketing data in BigQuery: write clean SQL, create partitioned and clustered tables, and manage scheduled queries while monitoring cost.
• Develop Python scripts to ingest data from platforms such as GA4, Google Ads, Meta and others, handling authentication, pagination, rate limits and retries.
• Automate pipeline execution and scheduling to keep reporting fresh without manual intervention.
• Implement data validation, monitoring and alerting to catch broken pipelines or stale data early.
• Document data sources, transformation logic and dashboard definitions for knowledge sharing.
• Collaborate with analysts and account teams to translate reporting requests into data models and dashboards, providing guidance on optimal solutions.

Required profile

• 3+ years of hands‑on experience as a Data Engineer.
• Strong communication skills – able to turn vague marketing questions into clear data models and explain results to non‑technical stakeholders.
• Familiarity with marketing/advertising data, at minimum GA4 and Google Ads.

Required skills

• SQL expertise, especially with BigQuery (scheduled queries, partitioning, clustering, cost‑aware querying).
• Data Studio – proven ability to design, build and maintain dashboards.
• Python for automation and light ETL, including REST API integration and authentication.
• Experience with marketing platforms such as GA4, Google Ads, Meta, TikTok, DV360, LinkedIn.

What we offer

• Great work culture and environment.
• Employee growth and development opportunities.
• Exposure to latest technologies, teams and tools.
• World‑class best practices.