Data Engineer at Dreamdata

Copenhagen, Capital Region of Denmark, Denmark -

Full Time

Start Date

Immediate

Expiry Date

21 Jan, 26

Salary

0.0

Posted On

23 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Data Infrastructure, Data Pipelines, Data Transformation, Data Enrichment, Monitoring, Apache Beam, Dataflow, Batch Processing, Streaming Pipelines, Blob Storage, Databases, Parquet, Go, Python, Google Cloud Platform

Industry

Software Development

Description

About Dreamdata Dreamdata is the industry leader in B2B marketing attribution and revenue optimization. We're on a mission to help B2B marketing leaders finally connect their efforts directly to real revenue - solving a complex problem that plagued the industry for years. Founded in 2019 by ex-Trustpilot (TRST:LSE) product and engineering leaders, Dreamdata was born from a real-world need, building the platform they always wished they'd had. It's working. We have achieved strong product-market fit and are experiencing explosive, triple-digit YoY growth. This momentum is now backed by a recent $55,000,000 Series B funding round set to fuel our rocketship as we scale globally. We are expanding rapidly and looking for exceptional, top-tier talent to help us build the future of B2B marketing. The Opportunity We are expanding the product team in our Copenhagen office to further empower our customers and ensure their success. This is where you come in! As an Data Engineer, you will work on our Platform Engineering team. You will ensure that the data pipelines and infrastructure running in Google Cloud can scale to the needs of our growing customer base. Key responsibilities Improve and maintain data ingestion pipelines that produce 60-80 events per second Own data transformation and enrichment (Dataflow) Monitoring the health and ensuring uptime for highly available services You'll thrive in this role if you: Have 4+ years of experience in data or software engineering, including experience building and scaling data infrastructure Have owned complex production data pipelines and understand how to monitor, operate, and evolve them over time Have worked with data processing engines like Apache Beam / Dataflow Understand the difference between batch and streaming pipelines and when to use each Have experience with different data storage technologies from blob storage (e.g. S3, GCS), to databases (OLAP/OTLP), to file formats (Parquet/DuckDB) Take ownership from design to deployment, and make pragmatic decisions independently Know how to strike a balance between velocity and over-engineering Are excited about delivering real value to users Our stack is based on GCP: Dataflow/Apache Beam, BigQuery, Cloud Storage, Cloud SQL and Google Kubernetes Engine. Most APIs and services are in Go, with data science tools and services in Python. Temporal is also leveraged to schedule and execute durable workloads. If you think the role sounds exciting, but you don't match all points please consider applying anyway. Location: Our office is located in the heart of Copenhagen with a sea view Ownership: Equity in a growing company. Lunch: Delicious lunch available in our canteen Inclusive Culture: Be part of a supportive and dynamic team making an impact in the B2B marketing space Private insurance: Private health insurance that comes with our pension plan Office dogs At Dreamdata, you’ll have the opportunity to make a real impact. Join us in shaping the future of B2B marketing analytics and activation while developing your skills and growing your career. We are committed to creating an inclusive, diverse workplace where everyone can thrive. If you’re passionate about building meaningful connections and helping businesses succeed, we’d love to hear from you.

Responsibilities

As a Data Engineer, you will work on the Platform Engineering team to ensure that data pipelines and infrastructure in Google Cloud can scale to meet customer needs. You will improve and maintain data ingestion pipelines and monitor the health of highly available services.