Senior Data Engineer

Fdj United; Stockholms kommun; Presencial; SEK 900 000 - 1 300 000; Tempo integral

Resumo da oferta

Fdj United in Sweden is seeking a Senior Data Engineer to build and optimize scalable ETL/ELT pipelines across a multi-cloud platform using Python, Spark, Airflow, and dbt. You will work within an agile team to modernize our data platform and enable real-time insights.

The role emphasizes data quality, observability, and CI/CD practices to ensure reliable data contracts and scalable lakehouse architectures on S3/Athena/Redshift.

Qualificações

• 5+ years of data engineering experience.
• Strong Python and SQL skills, plus Airflow, Spark/PySpark, dbt, and CI/CD proficiency.
• Experience with Lakehouse architectures and cloud data warehouses (S3, Athena, Redshift).
• Data quality frameworks, monitoring, and schema evolution expertise.

Responsabilidades

• Pipeline Development: Build ETL/ELT pipelines (Python, SQL), optimize Spark/PySpark jobs, manage Airflow DAGs, and implement dbt transformations.
• Lakehouse Architecture: Design medallion-style architectures using S3 and modern table formats (Iceberg, Delta Lake) with optimized layouts.
• Platform Infrastructure: Create reusable frameworks, enforce data contracts, build CI/CD pipelines, and establish observability practices.
• Data Quality: Implement validation frameworks, data contracts, and SLIs/SLOs for critical pipelines.

Conhecimentos

5+ years data engineering

Python

SQL

Airflow

Spark/PySpark

dbt

CI/CD

Data quality frameworks

Ferramentas

S3

Athena

Redshift

Iceberg

Delta Lake

Descrição da oferta de emprego

A hands-on engineering role building and optimising scalable ETL/ELT pipelines and Lakehouse architectures across a modern multi-cloud platform using Python, Spark, Airflow, and dbt.

Requires 5+ years of data engineering experience with strong expertise in SQL, CI/CD, data quality frameworks, and cloud technologies (S3, Athena, Redshift), with a plus for streaming and AI tooling experience.

Overview

A Senior Data Engineer position within an agile team, focused on building scalable data pipelines and modernizing a multi-cloud data platform. The role involves working with streaming technologies, Lakehouse architectures, and leveraging automation/AI to improve efficiency.

What you will do

• Pipeline Development: Build ETL/ELT pipelines (Python, SQL), optimize Spark/PySpark jobs, manage Airflow DAGs, and implement dbt transformations.
• Lakehouse Architecture: Design medallion-style architectures using S3 and modern table formats (Iceberg, Delta Lake) with optimized layouts.
• Platform Infrastructure: Create reusable frameworks, enforce data contracts, build CI/CD pipelines, and establish observability practices.
• Data Quality: Implement validation frameworks, data contracts, and SLIs/SLOs for critical pipelines.

Your experience

Required

• 5+ years in data engineering
• Strong Python, advanced SQL, Airflow, Spark/PySpark, dbt, and CI/CD proficiency
• Experience with Lakehouse architectures, dimensional modeling, and cloud data warehouses (S3, Athena, Redshift)
• Data quality frameworks, monitoring, and schema evolution expertise

Nice-to-Haves

• AI coding assistants (Cursor, Claude Code, Copilot)

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