Senior Data Engineer Agentic Data Integration

Why This Role Matters

At Funnel we ingest marketing data from hundreds of external APIs across thousands of customers. The challenge isnt just moving data its making sense of it when schemas change without warning metrics vary by source and pipelines break in ways we cant fully control.

In this role youll 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 youll design and build systems that handle messy fast-changing external data and turn it into reliable analytics-ready datasets. Youll work on problems that dont 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 Funnels data platform

Skills & Experience Were 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 skillsable 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 were 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 3000 businessesincluding brands like Adidas and Sonymake 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 dataand solves the challenge of making it reliable and useful for decision-making.