Data Platform Engineer

Copenhagen - Denmark

Monthly Salary: DKK 720000 - 840000

Experience Required: 4-5years

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

We re supporting a growing product-led company in Copenhagen who are looking to hire a Senior Data Engineer to join their Data Engineering this role you ll help build and evolve a streaming-first self-service data platform working closely with internal developers analysts and data scientists. The position is hands-on at first (stream/batch pipelines reusable patterns documentation co-engineering) then gradually shifts into more of an advisory and enablement capacity as adoption across the business matures.

This is an on-site position in Copenhagen (Nordhavn area). The company offers daily lunches health insurance and a collaborative energetic environment. Relocation is not offered for this role.

Key Responsibilities

Build initial stream/batch processing pipelines and reusable patterns to support adoption.
Develop documentation templates examples and reference implementations.
Lead onboarding training sessions and workshops.
Support developers and analysts with complex scenarios and edge cases.
Transition from initial ownership to advisory/support as internal users gain maturity.

Technical Experience

Stream Processing & Data Engineering: Apache Flink Spark Beam.
Pipelines: Building/optimizing streaming & batch transformations joins enrichments.
Data Modeling & Schema Management: Schema Registry Avro Protobuf JSON Schema schema evolution star-schema OBT.
Analytics & Operations: Understanding of analytical use cases dashboards real-time applications. Exposure to SQL Databricks SQL Snowflake BigQuery Looker Tableau DBT.
Documentation & Communication: Technical documentation user guides tutorials. Ability to explain technical concepts across varied audiences.

Nice-to-Have

Proactive customer-centric mindset.
Strong interpersonal skills to collaborate with stakeholders.
Experience delivering training/workshops.
Mentorship and guidance in complex scenarios.

Preferred Qualifications

4 years experience in Data Engineering / Analytics Engineering / Developer Advocacy.
Background in enablement consulting or advisory roles.
Track record of driving adoption and maturity of self-service data platforms.

Benefits

Medical insurance
Daily lunches health insurance social events and more.

Apache Flink, Big Query, DataFlow

We re supporting a growing product-led company in Copenhagen who are looking to hire a Senior Data Engineer to join their Data Engineering this role you ll help build and evolve a streaming-first self-service data platform working closely with internal developers analysts and data scientists. T...

Key Responsibilities

Build initial stream/batch processing pipelines and reusable patterns to support adoption.
Develop documentation templates examples and reference implementations.
Lead onboarding training sessions and workshops.
Support developers and analysts with complex scenarios and edge cases.
Transition from initial ownership to advisory/support as internal users gain maturity.

Technical Experience

Stream Processing & Data Engineering: Apache Flink Spark Beam.
Pipelines: Building/optimizing streaming & batch transformations joins enrichments.
Data Modeling & Schema Management: Schema Registry Avro Protobuf JSON Schema schema evolution star-schema OBT.
Analytics & Operations: Understanding of analytical use cases dashboards real-time applications. Exposure to SQL Databricks SQL Snowflake BigQuery Looker Tableau DBT.
Documentation & Communication: Technical documentation user guides tutorials. Ability to explain technical concepts across varied audiences.

Nice-to-Have

Proactive customer-centric mindset.
Strong interpersonal skills to collaborate with stakeholders.
Experience delivering training/workshops.
Mentorship and guidance in complex scenarios.

Preferred Qualifications

4 years experience in Data Engineering / Analytics Engineering / Developer Advocacy.
Background in enablement consulting or advisory roles.
Track record of driving adoption and maturity of self-service data platforms.

Benefits