Senior Data Engineer

Hi, I'm Nishya, Head of Data and AI at Intact – the world's leading software provider for the Testing, Inspection and Certification (TIC) industry. We're looking for a Senior Data Engineer to build the data foundation for the next generation of our product.

We have years of operational data on audits, certifications, standards, evidence, findings and organizations. Much of it is still locked in systems built to run workflows. We want to turn it into a trusted, scalable product asset.

You'll design the pipelines, models, quality checks, and infrastructure that make this data ready for analytics, product features, and AI/ML.

This is not a reporting role or a ticket queue. You'll help build a modern data platform that becomes part of the product itself. It will connect legacy and modern systems as Intact transforms domain by domain. You'll work closely with me and with our Product, Engineering, and Applied AI/ML teams.

Sounds exciting? We'd love to hear from you.

ARE YOU READY?

• Build reliable, scalable, and cost-efficient batch and incremental data pipelines, with near-real-time processing where it's needed.
• Own Change Data Capture (CDC), incremental processing, and schema evolution, and make sure the data's history stays correct.
• Own data contracts with source teams so schema changes stay manageable.
• Design canonical analytical models for key business entities, events, and relationships.
• Build reusable transformations with clear layers between raw, transformed, and consumption-ready data.
• Design the data platform around how consumers use it, balancing performance, scalability, and cost.
• Build and evolve the data quality and governance framework, covering testing, monitoring, lineage, ownership, and failure recovery.
• Build self-serve patterns and documentation so teams can publish and consume data independently.
• Provide trusted data for analytics, product features, and AI/ML use cases.
• Design mechanisms for access control, retention, deletion, anonymization, and pseudonymization.
• Monitor data pipelines and keep them fast and cost-efficient.
• Treat data engineering as software engineering, with version control, code review, automated testing, infrastructure as code, and CI/CD.

ARE YOU THE ONE?

We care more about how you approach problems than about which tools you've used. Here's what we have in mind.

Technical foundation

• 7+ years of building and running production data systems, ideally owning them from source to consumer.
• Advanced SQL and Python (or another data engineering language), with a solid understanding of how your queries perform.
• Clean, well-tested code that your teammates can easily maintain.
• Strong dimensional, relational, and analytical data modeling, including tracking how data changes over time.
• A degree in computer science, data engineering, or a related field, or equivalent practical experience.

Architecture and data platforms

• Hands-on CDC experience (e.g., Debezium, AWS DMS, Fivetran, or native log-based CDC), including handling deletes, backfills, and schema changes.
• Experience designing a modern cloud warehouse or lakehouse (e.g., Snowflake, Databricks, BigQuery, or Microsoft Fabric) with a strong focus on performance, scalability, and cost.
• Experience with reusable ELT transformations (e.g., dbt) and orchestration tools (e.g., Airflow or Dagster).
• Pipelines that can be rerun safely and recover predictably from failures.
• A strong batch background, and the judgment to know when near-real-time processing (e.g., Kafka or a managed equivalent) is worth the extra complexity.

Running data in production

• Docker, Terraform (or similar), and CI/CD as part of your everyday toolkit.
• Monitoring, logging, and alerting built into everything you ship.
• Cost and performance considered in every design decision.
• Data quality, security, and governance built in from the start, covering contracts, validation, lineage, access control, and ownership.
• A good understanding of privacy requirements such as the GDPR, including retention, deletion, and pseudonymization.

How you work

• You're a systems thinker with pragmatic judgment and a strong sense of ownership, from design through operation.
• You prefer simple solutions that deliver value early over complex ones that take months to land.
• You're curious about the business meaning behind the data.
• You speak up when you see a better way and stay open to other people's ideas.
• You're fluent in English. German is a plus.

Nice to have

• Experience with open table formats such as Apache Iceberg or Delta Lake.
• Experience with a data catalog or lineage tool such as DataHub or OpenMetadata.
• Experience preparing data for AI/ML, such as evaluation datasets, features, or retrieval pipelines.
• Experience moving data out of legacy, workflow-oriented systems while they're still in use.
• Experience consolidating data from many similarly structured source databases into a single analytical model.

WHY US?

• A platform to shape. As one of the first data engineers in the Data and AI team, you'll help shape the platform and its standards from the start.
• Work with purpose. Your work helps safeguard quality, safety, and sustainability worldwide.
• An international team. You'll work closely with colleagues across Product, Engineering, and operations around the world.
• Flexible work. Flexible work models, with a 100% remote option.
• Lebring office perks. Food vouchers, free parking, and easy access to public transport.
• Room to grow. We don't just allow personal development, we encourage it. Your growth is our gain.
• Fair compensation. From €64,554 gross per year (full-time), with overpayment up to €85,000 depending on seniority and experience.
• Start: As soon as possible.