Senior Data Engineer (remote)

Qualifyze

1d • Remote

About The Position

Qualifyze is seeking a Senior Data Engineer to join its Product & Tech team and help build and evolve its data platform. The role owns key pipelines and data products end to end and contributes to engineering decisions that shape the platform. Its central focus is designing, building, and maintaining reliable data pipelines across operational databases and the analytical platform, using sound software engineering practices. The engineer will collaborate with product and backend engineering teams and work directly with business stakeholders who rely on accurate, timely data for product decisions.

Qualifyze is a supply chain compliance management company in the Life Sciences industry, founded in 2019. Its digital solutions connect manufacturers and suppliers with a global network of auditors and quality experts. The company reports serving more than 1,500 pharmaceutical and healthcare companies and having conducted over 4,500 audits across more than 85 countries.

The role is suited to someone with strong Python and SQL skills, solid software engineering fundamentals, and hands-on experience building production data pipelines in a product or platform team. The position is listed as remote, while the benefits section describes a hybrid working mode and the option to work from anywhere for up to three months of the year.

Requirements

• Proficiency in Python for data engineering, including building robust ETL/ELT pipelines and reusable modules, with strong testing practices such as pytest and good observability.
• Strong SQL skills with PostgreSQL, including complex query design, performance tuning, indexing, and reading execution plans for both OLTP and OLAP workloads.
• Hands-on experience with dbt, including building, testing, and documenting models; experience with a layered project structure such as medallion is ideal.
• Experience with Dagster or a similar orchestrator such as Airflow, including building assets or jobs, scheduling, monitoring, and handling failures in production workflows.
• Working knowledge of Docker and Kubernetes for packaging and running data services and batch jobs in production.
• Solid grasp of data modeling, including dimensional modeling and the trade-offs between operational and analytical schemas.
• Strong software engineering fundamentals and hands-on experience building production data pipelines in a product or platform team.

Nice To Haves

• Experience with AWS, including S3, EKS, or Secrets Manager.
• Experience with database schema migration tools such as Liquibase or with data contracts.

Responsibilities

• Design, build, and maintain scalable, reliable, and well-tested data pipelines and data products.
• Manage features and pipelines end to end, from schema design in operational databases through ingestion and transformation to delivery of analytical datasets.
• Contribute to the architecture of the data platform and help evaluate technical trade-offs with the team.
• Apply and help improve standards for data modeling, data quality, testing, and code review.
• Work with Product, Engineering, and business stakeholders to translate requirements into well-scoped data solutions.
• Monitor, troubleshoot, and resolve pipeline incidents, and improve observability and reliability over time.
• Share knowledge with the team and mentor fellow engineers through pairing and code reviews.

Benefits

• Competitive compensation package, reviewed annually.
• Country-specific vacation package that increases with tenure.
• Country-specific benefits, including private health care, fitness allowances, and meal allowances.
• Annual personal development budget.
• Hybrid working mode, with the option to work from anywhere for up to three months of the year.
• Equipment and tools to work effectively.
• Annual in-person company event and celebration in Europe.
• Opportunity to work with an exceptional team.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed