Key Skills

Job Description

Studytube makes professional development accessible, easy and actually enjoyable. Behind that platform sits a growing stream of learning data, and we want to put it to work for our customers, our product teams, and the AI-powered features we are building next. We are looking for a Data Engineer who likes ownership. You will be the engineering backbone of a small data team: you turn messy source data into models people trust, and you leave the platform better than you found it. The role You join the Product & Tech team as the data engineer in a team of three, working side by side with data analysts. The team will grow. Over time a dedicated data team with a Data Lead is likely. For now, you report to the Head of Engineering and you own our data platforms end to end. That means real scope. You design, build and run the pipelines that take raw product and business data through to the marts that power analytics, reporting and product features. You talk to analysts, product managers and engineers, translate what the business needs into something that actually works, and keep quality non-negotiable: tests, monitoring and documentation are part of the job. Part of our platform already runs on Databricks: a dedicated Azure environment for customers with strict security requirements. You will take ownership of it, working alongside the external specialists who built it until you run it independently. Next, you will help prepare our main warehouse move from Snowflake towards Databricks. What You Will Do Own our main Snowflake warehouse: ingestion, transformation, modelling and the marts analysts and product teams rely on. Own our Databricks environment on Azure: pipelines, access, cost and daily operations, in a setup with strict security and compliance requirements. Build end-to-end pipelines that are incremental where it matters, idempotent, tested and documented. Bring structure to what we have today: clean up the current architecture, tighten conventions and make the platform easier to extend. Ingest new sources via Fivetran or custom connectors, including the quirks that never make it into the docs. Run dbt Cloud jobs with clear dependencies, scheduling and failure handling. Monitor freshness, volume and schema drift, and do a proper root-cause analysis when something breaks. Help Studytube measure what matters: support the implementation of use-case metrics the business can actually act on. Work GDPR-aware: access, sensitivity, retention and deletion are part of how you design. Who You Are You have about 3–6 years of hands-on experience as a data engineer or analytics engineer in production. This is not a role with a large platform team behind you. You can take a new source or an analytical need and deliver a tested, monitored solution without someone looking over your shoulder. You are comfortable in a scale-up: enough calm to handle a bit of chaos, and enough craft to put structure in place. You can explain trade-offs (batch vs streaming, incremental vs full refresh, build vs buy) to people who do not live in SQL all day. And you treat data as a product: if an analyst cannot find, understand or trust a table, the work is not done. You bring Production experience with Databricks (Delta Lake, Unity Catalog), ideally on Azure. Strong SQL and production dbt (Cloud). Snowflake or comparable warehouse experience. Fivetran or custom connectors for ingestion. Working Python and a normal Git workflow: branches, pull requests, code review. A testing mindset: data tests by default. An eye for cloud cost. Confidence to take over a platform from external consultants. Clear English, written and spoken. You own your backlog and flag when plans change. Willing to undergo Dutch security screening (VGB). Nice to have Terraform or other infrastructure-as-code. A warehouse migration, ideally Snowflake to Databricks. Looker / LookML or data contracts. Experience in regulated or public-sector environments. B2B SaaS experience, or AI tools in your workflow. Our stack Snowflake as our main warehouse today, with a likely move to Databricks. Databricks on Azure for a dedicated, high-security environment. Some BigQuery on the side. dbt Cloud for transformation and orchestration. Fivetran for ingestion. Looker and Metabase for reporting. Python and Git throughout. What We Offer A competitive salary and the space to shape how data engineering is done at Studytube. The flexibility to own your schedule with hybrid working (3 days at our IJ-view office, 2 from home) 25 days of holiday to recharge, plus a free day to celebrate your birthday A solid 3% pension contribution via a.s.r., fully covered by Studytube A €1,000 annual learning budget, with 50% available for wellbeing or perfecting your home office Continuous growth via our own LevelUp Academy on the Studytube platform Access to our in-house Studygym, making that Basic-Fit subscription unnecessary Work from a stunning brand-new office in the Houthavens overlooking the water A MacBook Air for your best work and a €10 monthly phone allowance Healthy, fully catered lunches available for a small personal contribution Quarterly team adventures and a legendary annual company party About Studytube We help organisations invest in their people with an all-in-one learning platform. More than 300 customers already use it, including Bol.com, ASR, CZ, Manpower and VolkerWessels. Together with 200+ colleagues we want to become Europe’s number one platform for professional development. Does this sound like a match? Apply via this vacancy. Questions about this role are welcome at [email protected] .

Core Responsibilities

Own and operate the Snowflake warehouse and Azure Databricks environment, building and maintaining tested, monitored, documented data pipelines, transformations, and analytics marts. Improve platform architecture and data quality, support business metrics and GDPR-aware practices, and help prepare the migration from Snowflake to Databricks.

Requirements

Candidates should have approximately 3–6 years of production experience in data or analytics engineering, with strong SQL and dbt Cloud skills and hands-on experience with Databricks, preferably on Azure. They should also be comfortable with Snowflake or a comparable warehouse, ingestion tools, Python, Git, testing and monitoring, and independently owning platform work; Dutch security screening is required.

Benefits

• Hybrid Working
• 25 Days Of Holiday
• 3% Employer-Funded Pension Contribution
• €1,000 Annual Learning Budget
• Wellbeing Budget
• In-House Learning Academy
• In-House Gym
• MacBook Air
• €10 Monthly Phone Allowance
• Catered Lunches
• Team Events