Why This Role Matters

At Funnel, we ingest marketing data from hundreds of external APIs across thousands of customers. The challenge isn’t just moving data, it’s making sense of it when schemas change without warning, metrics vary by source, and pipelines break in ways we can’t fully control.

In this role, you’ll help build a new kind of data integration layer- systems that can understand, validate, and adapt as data evolves- making messy data usable and trustworthy at scale.

About the Role

As a Senior Data Engineer, you’ll design and build systems that handle messy, fast-changing external data and turn it into reliable, analytics-ready datasets. You’ll work on problems that don’t have predefined solutions- shaping how our data platform evolves to become more adaptive and resilient over time.

This role sits at the intersection of data engineering and system design, with a strong focus on robustness, data quality, and long-term scalability.

Our Ways of Working

We organize our work around domains and workstreams instead of traditional teams. Domains define clear areas of ownership, while workstreams form around shared goals and outcomes. This way of working helps us reduce dependencies, collaborate more naturally, and move faster with greater autonomy. We focus on delivering meaningful impact, learning through iteration, and continuously improving together. Read more about how we work →

What You Will Do

• Build and maintain data integrations that handle changing APIs and inconsistent data sources

• Design and build the ingestion layer that transforms raw, unstructured data in to structured, storage-optimized formats (e.g. Parquet) ready for downstream processing

• Detect and handle schema changes, missing data, and inconsistencies in ingestion pipelines

• Improve how data quality is defined, measured, and maintained across systems

• Contribute to systems that can adapt to evolving data structures over time

• Explore opportunities to automate and make data workflows more intelligent

• Collaborate with engineers and product to shape the future of Funnel’s data platform

Skills & Experience We’re Looking For

• 5+ years of experience in data engineering, with clear ownership of production systems

• Strong Python skills (e.g. Pandas, Polars) and ability to write maintainable data processing code

• Hands-on experience with lakehouse architectures (e.g., S3, Iceberg, Spark or Trino)

• Deep understanding of table formats (Apache Iceberg), schema evolution, and columnar data formats (Parquet, Arrow)

• Experience in AI-assisted workflows, including LLM-driven transformations, with a pragmatic approach to reliability and explainability

• Proven experience building and operating data pipelines that handle unreliable or evolving data sources

• Strong system design skills—able to make trade-offs and design for long-term scalability and resilience

Please note: For this role, we are not considering interns or new graduates for the position.

Curious to know more about the data problems we're solving? Read more on our Dev blog, an article written by our CTO, Jonas Björk and Engineering Manager, Anirudh Mehta

Location & Eligibility

At this time, we only consider applicants who are already based in Stockholm and meet one of the following criteria:

• Hold Swedish citizenship

• Hold EU/EEA citizenship and are currently living in Stockholm

• Have a valid Swedish work permit

The Hiring Process -

1. Screening Interview – Initial conversation to get to know each other and align on expectations

2. Technical Interviews – Deep dive into your experience with data engineering, system design, and problem-solving. Hands on agentic development and coding.

3. Offer!

About Funnel

Funnel is a Marketing Intelligence platform that helps over 3,000 businesses—including brands like Adidas and Sony—make sense of their marketing data.

With offices in Stockholm, Boston, Hamburg, and Sydney, we operate with an office-first culture where we collaborate in person 4 days a week. Our culture is built on being transparent, collaborative, and focused on achieving together.

Under the hood, our product deals with large volumes of inconsistent, fast-changing external data—and solves the challenge of making it reliable and useful for decision-making.