Senior Data Engineer (Python/SQL)

Location: Stockholm, Sweden; hybrid with at least 3 days per week in the office and 2 days at flexible work locations

Company

hirify.global is a video advertising technology company helping brands reach audiences on the open web while enabling publishers to generate sustainable revenue.

What you will do

• Run and evolve the data platform end to end, from ingestion and transformation through modelling and serving.
• Build reliability through data-quality checks, monitoring, alerting, idempotent pipelines, backfills and repair tooling.
• Work with high-volume event and streaming data, third-party APIs, operational databases and files.
• Build governed models, onboard new data sources, retire legacy paths and expand self-service through curated datasets.
• Develop trusted data products for campaign, commercial and financial reporting, billing, reconciliation, product insight and operational decisions.
• Partner with teams across the business to turn ambiguous data needs into valuable use cases and improve platform operations, including pragmatic use of AI tools.

Requirements

• Substantial experience building and operating production data platforms.
• Strong Python and advanced SQL skills.
• Experience building and operating orchestrated production data pipelines; Airflow experience is strongly preferred.
• Experience with cloud environments at meaningful scale, ideally GCP, plus data lakes, data warehouses and complex dimensional models.
• End-to-end ownership of production systems with a focus on reliability, data quality, performance and cost efficiency.
• Clear communication, independent work style and practical ability to evaluate AI-generated engineering output.

Nice to have

• Experience with ClickHouse, Kubernetes/GKE or Terraform.
• Experience with high-volume event, impression or streaming data.
• Experience in ad tech, martech, media measurement or another commercially complex data domain.
• Experience decommissioning legacy systems or building AI/LLM-backed tooling and data products.

Culture & Benefits

• Hybrid workplace policy with a 3:2 split between office collaboration and flexible work locations.
• Collaborative R&D organisation spanning Product, Engineering, Design, Data and Infrastructure.
• Values focused on discovery, ownership and achieving results together.
• Continuous application review and interviews.
• Background checks are conducted for all hires to meet customer requirements and protect business-critical information.

Hiring process

• Applications and interviews are reviewed continuously.
• Background checks are completed for all hires.