Real-Time Data Engineer — AWS & Data Mesh

Cph Ai Hub; Hørsholm; Remote; DKK 600.000 - 900.000; Vollzeit

Zusammenfassung

Trackman is hiring for a data engineering role in Denmark, focused on real‑time athlete data delivered via cloud services. You will build high‑reliability data pipelines using AWS, Python and DBT, collaborate with data science and BI teams, and contribute to scalable data architectures.

The team embraces GitOps and Agile practices. You will optimize data flows, troubleshoot quality issues, and design solutions that scale with demand, while aligning with business needs and product goals.

Qualifikationen

• Background in Computer Science or equivalent technical field.
• Experience with cloud native technologies on AWS.
• Experience with Python, Linux and Docker.
• Familiarity with SQL and databases.
• Interest in big data, NoSQL and data warehouse solutions.
• Interest in machine learning and running large scale ML operations.
• Familiarity with GitOps process.

Aufgaben

• Use developer skills to work on an AWS cloud stack with Python microservices and DBT at its core.
• Contribute as an SRE and ensure platform reliability meets product needs.
• Architect solutions and pipelines to solve data at scale.
• Identify and troubleshoot data quality or platform issues using systematic methods.
• Interface with business, operations and other development teams to refine requirements.

Kenntnisse

Data engineering

Backend development

DevOps

GitOps

Agile

Automation

English

Tools

AWS

Python

Linux

Docker

DBT

CloudFormation

AWS SAM

Lambda

ECS

API Gateway

Step Functions

Redshift

S3

KDS

SQL

NoSQL

Data warehouse

Machine learning

Jobbeschreibung

Trackman is hiring for a data engineering role in Denmark, focused on real‑time athlete data delivered via cloud services. You will build high‑reliability data pipelines using AWS, Python and DBT, collaborate with data science and BI teams, and contribute to scalable data architectures.

The team embraces GitOps and Agile practices. You will optimize data flows, troubleshoot quality issues, and design solutions that scale with demand, while aligning with business needs and product goals.