Senior Data Engineer

• Love to build end-to-end data solutions - from collection (front-end tracking, APIs) through pipelines, storage, analytics, and automated insights.
• Enjoy connecting systems like Snowplow, Databricks, and Power BI to create a single source of truth for business and product teams.
• Care deeply about data quality, documentation, versioning, and automation, not just raw pipelines.
• Take pride in maintaining a robust development lifecycle (Dev QA Prod) for data.
• Thrive in cross-functional collaboration with teams like Sales, Finance, Product, and Operations.
• Are motivated by designing scalable architectures that fuel business growth and innovation., * Designing, developing, and maintaining scalable data architectures using Databricks, Azure Data Factory, AWS (S3, RDS), and Azure Cosmos DB.
• Managing ETL/ELT pipelines that integrate event data (Snowplow), app data (FMP1/FMP2), and external sources (HubSpot, MoneyBird, GA, Firebase, KNMI, etc.)
• Building CI/CD for data engineering - versioned workflows, automated testing, and deployment pipelines in GitHub + Databricks.
• Defining QA and data validation frameworks to ensure data accuracy, reproducibility, and governance across environments.
• Owning the orchestration layer, scheduling, and monitoring via Databricks Jobs, Azure Data Factory, or equivalent tools.
• Designing and optimizing data models for analytical workloads (Synapse / BigQuery), including schema evolution, partitioning, and query tuning.
• Supporting analytics and product teams by delivering curated, reliable datasets and collaborating on BI dashboards (Power BI / Looker).
• Documenting the data ecosystem - lineage, naming conventions, transformation logic, and schema definitions.
• Proactively identifying bottlenecks, tech debt, or scalability risks and proposing improvements.

Do you have experience in Usability?, * Prefer "business as usual" over change

• Want a team where mediocre is okay
• Have never worked remotely and think async means "lonely"
• Are waiting for permission instead of taking initiative, * 5+ years of experience as a Data Engineer, Analytics Engineer, or Full-Stack Data Developer in cloud-native environments.
• Deep experience with Python, SQL, and Spark (PySpark/Databricks).
• Familiar with data modeling (Kimball/Star schema) and modern ELT practices.
• Hands-on with data orchestration and CI/CD for data workflows (e.g., Databricks Workflows, Airflow, Azure Data Factory).
• Knowledge of version control (Git) and data documentation tools (dbt docs, DataHub, or similar).
• Understanding of data quality frameworks (Great Expectations, Soda, custom validation).
• Skilled in data visualization and integrating pipelines into BI tools like Power BI or Looker
• Strong communicator who can translate technical insight into business context.
• Curious, organized, and relentlessly focused on improving data usability and reliability.
• Comfortable in a fully remote, asynchronous environment and passionate about continuous learning., * Experience with event tracking pipelines (Snowplow, Segment, GA4).
• Exposure to data contracts and schema governance.
• Familiarity with streaming architectures (Kinesis, Kafka).
• Experience optimizing Databricks Unity Catalog or Azure Synapse Analytics.
• Knowledge of machine learning pipelines or data products is a plus.

• A competitive salary
• 25 vacation days + your local national holidays
• A top-tier MacBook and remote-ready gear
• Monthly wellness budget to invest in your health
• Co-Working allowance
• Events, training, or courses that directly and primarily contribute to your work at Publitas
• Free books on Kindle and Audible
• Free Publitas Swag (merchandise)

We are Publitas! We're a remote-first, fast-growing SaaS company helping brands turn static content into digital discovery experiences that drive results.