Senior Data Platform Engineer - Production-Scale & AI

SeenThis; Stockholms kommun; On-site; SEK 900,000 - 1,200,000; Full time

Job summary

SeenThis is seeking a data engineer to join the R&D data team, owning and evolving the production data platform across ingestion, transformation and serving. You will partner with product, engineering and analytics to turn diverse data into governed models and actionable insight.

You will lead end-to-end development, improve reliability, and apply AI tools judiciously. A strong focus on scalable, cost-efficient data architecture is essential.

Qualifications

• Extensive experience building and operating production data platforms.
• Strong Python and advanced SQL skills; proven data pipeline design with Airflow.
• Experience with cloud platforms (GCP preferred) and cost/performance optimization.

Responsibilities

• Run and evolve the data platform end to end, from ingestion through transformation, modelling and serving.
• Make it reliable through data-quality checks, monitoring and alerting, idempotent pipelines, backfills and repair tooling.
• Work with data of varying shapes and scales, from high-volume events to APIs and databases.
• Build and evolve governed models, onboard new sources, retire legacy paths and expand self-service through curated datasets.
• Produce trusted data products for campaign, commercial, billing, and operational reporting.
• Collaborate with SeenThis teams to translate problems into data use cases and drive solutions.
• Improve platform operations using AI where beneficial.

Skills

Python

SQL

Airflow

GCP

Data lakes

Data warehouses

Production systems

End-to-end ownership

AI tooling

Communication

Tools

Kubernetes/GKE

Terraform

BigQuery

Job description

SeenThis is seeking a data engineer to join the R&D data team, owning and evolving the production data platform across ingestion, transformation and serving. You will partner with product, engineering and analytics to turn diverse data into governed models and actionable insight.

You will lead end-to-end development, improve reliability, and apply AI tools judiciously. A strong focus on scalable, cost-efficient data architecture is essential.