[Hiring] Data Engineer @Synera GmbH

Role Description

We are building an internal superagent: an AI layer over all of Synera's business data and tools that every employee can delegate work to. Its intelligence is only as good as the data underneath it, and that data foundation is yours to own, build, and shape.

• Own the data warehouse (Timescale): Synera's single source of truth for data, its design and development to always be cutting edge.
• Extract data from our GTM and business systems (Salesforce, HubSpot, product, finance, ...) into our data warehouse reliably, and structure & annotate it so it can be queried.
• Build and own data flows: ETL pipelines (Airflow/Timescale), data models, and the sync jobs that keep systems consistent.
• Turn data into foresight: build the reporting and forecasting layer (Power BI, Salesforce reports, forecast models) that leadership runs on and extrapolate from pipeline, funnel, and usage data to where the business is heading.
• Make the data agent-ready: model and expose it (warehouse models, APIs, MCP connectors, permissions, governance) so AI agents, and ultimately our superagent, can consume it.
• Build the retrieval layer for what is not in tables (documents, wiki content, tickets, meeting transcripts): chunking, embeddings, indexing.
• Engineer, don't improvise: transformations are version-controlled, tested, and documented.
• Treat data quality as a product: monitoring, validation, and hygiene are built in.
• Team enablement: partner with every team to get their data into the warehouse and into a state an agent can act on, and change how it gets created so machine-readable is the default.

Qualifications

• SQL is second nature; you have built ETL/data pipelines (Airflow or similar) and data models and are strong in data extraction and transformation.
• You have built the data layer behind LLM applications: retrieval, embeddings and vector search, context design, MCP and comparable tool interfaces.
• You have integrated multiple systems: APIs, webhooks, auth models, rate limits and unannounced schema changes.
• You can debug a discrepancy across three tools until you find which definition was wrong.
• You think about data access and privacy by default.
• An automator by instinct: scripts, APIs, workflow tools, and AI agents are how you scale yourself.
• You use LLMs as a daily working tool, not a novelty.
• You have built reporting and forecasting people actually use and know the difference between a dashboard and an answer.
• You work in English confidently; German is a plus.
• You communicate clearly with non-technical colleagues, sales reps, marketers, and executives alike.
• Ownership mentality: you document what you build, you notice what nobody asked about, and you would rather fix the system than the symptom.

Requirements

• In 3 months: you own the warehouse and its ingestion landscape end to end, the datasets the reporting and forecasting cycle runs on reconcile, and you have a prioritized map of the company data the superagent is missing.
• In 6 months: across Synera, data flows are documented, monitored, and trustworthy; team self-serve the answers they used to ask you for.
• In 12 months: your data foundation becomes the knowledge layer of Synera's superagent. AI agents across the company answer questions and execute work on data you made trustworthy.

Benefits

• Flexible working: you decide when & where to work (as long as you have a residency in Germany).
• Flexible public holidays: swap days off according to your values and beliefs!
• Home office setup support + access to our office in Bremen.
• Personal development budget of €2,000 to attend conferences and trainings or buy interesting books to improve in an area of your choice.
• We don't count your vacation days, as we trust all our team members to decide what's best for them and the company.
• Prefer two wheels over four? 🚲 We’ve got you covered with JobRad.
• To support your personal and professional well-being, we offer company fitness with Wellpass and mental health platform nilo.
• Regular team events, virtual coffee breaks, and spontaneous afterworks. We also get together as a whole company for 2-3 day off-sites twice a year! 🌈