16 open roles
Senior Data Engineer (w/m/d)
Job description
TL;DR Senior Data Engineer. Build our data foundation from v1 -> v10. Join the early core team of experienced entrepreneurs (scaled to millions of users, $100m+ exits). Build the future of tax & accounting with AI. Architect our data warehouse, build resilient pipelines, and enable our finance stack. Grow into leadership as we expand across countries.
Above-market pay + meaningful equity. THE OPPORTUNITY How taxation, accounting and payroll work today is a pain for everyone. Still every business must do it continuously. It is the backbone that our economy runs on. Enabled through AI, we are turning this often-painful process into a radically simple experience for our customers, so they can focus on what matters to them: growing their business.
ABOUT US
We are a team of experienced entrepreneurs who have scaled businesses to 10s of millions of users, 10s of millions in revenue, multiple countries, and 9-digit exits - and we are just getting started. We are backed by leading venture investors and expanding rapidly. THE ROLE As our first Data Engineer, you’ll be a core part of building the data architecture behind Skalar.
We are past the initial founding phase, but we are still very, very early - meaning pretty much everything you touch will involve greenfield building. While we provide a world-class professional service to our customers, data is our foundation. Your work will allow our future data analysts and scientists to shine in their work.
WHAT YOU’LL OWN - 0 → 1 and Beyond: Architect and build our greenfield data warehouse from scratch; take data infrastructure end-to-end.
- Core Data Pipelines: Build resilient ETL/ELT pipelines to fetch, clean, and transform massive amounts of financial data from messy third-party APIs and integrations.
- Integrity & Security: Establish rigorous data governance, quality checks, and security protocols to ensure absolute data integrity for highly sensitive financial & employee information.
- Leadership: Hire and mentor junior engineers (if interested); gain leadership experience as we grow. OUR TECH STACK (GREENFIELD)
- Prefer boring tech where it matters; innovate where it differentiates (especially in AI).
- Our product tech stack is currently TypeScript, Next.js (React) and PostgreSQL. You will have full freedom to select the best tech stack for our data warehouse (e.g., Snowflake/Big. Query, dbt, Airflow/Dagster).
- You’ll have a strong influence on tech, cloud, and architecture choices, specifically regarding data warehousing and orchestration.
- Tooling budget for whatever makes you fast. No legacy, no yak‑shaving. WHAT YOU’LL BRING - 5+ years of data engineering experience, with a standout track record of scaling modern data infrastructure (such as Big. Query, Snowflake, Looker and dbt)
- A bachelor’s or master’s degree in computer science or a related field
- You have expert-level SQL skills, strong programming skills in Python and proven experience setting up modern cloud data warehouses and orchestration tools
- You have deep experience dealing with complex third-party APIs, rate limits and asynchronous data fetching
- You have experience with agent frameworks (such as Lang. Chain) and RAG pipelines, and you use AI for nearly all coding tasks
- Very good written and verbal communication skills in English (min. C1), German is a plus
- You have a valid work permit to work in Germany WHAT YOU’LL GET
- Unique opportunity to join a company very early which you can shape
- Rapid growth path: Grow your career with the growing, AI-first company
- Perfect environment to develop relevant skills in a world of AI
- Above-market compensation + equity package, that has the potential to drastically gain in value THE PROCESS (FAST, MEANINGFUL, NO HOMEWORK)
- Jump on an intro call with a recruiter
- Get to know a fellow engineer, virtually or in person (up to you)
- Meet our whole founding team during a final interview (in-person, ~3h, incl. live coding)
Description copied from Skalar's careers page. Read the full posting before you apply.
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