Data Engineer (m/w/d)
Core
Building, developing, and operating modern data platforms and pipelines to integrate, process, store, and provide data for analytics, reporting, and machine learning.
Role type
Data Engineer
Builds
Scalable ETL/ELT pipelines, Data Warehouses, Data Lakes, and Lakehouse architectures
Domain
Data Engineering / Cloud Infrastructure
Deliverable
production ML models
Required skills
SQL, Python, relational database design, ETL/ELT processes, data modeling, Git, cloud technologies
Preferred skills
AWS/Azure/GCP, Databricks/Snowflake/Fabric, Apache Spark, Apache Airflow, Docker, Kubernetes, Terraform, CI/CD, Kafka, Data Governance
Technologies
Python, SQL, PostgreSQL, SQL Server, Oracle, Azure, AWS, Google Cloud, Databricks, Snowflake, Microsoft Fabric, Apache Spark, Apache Airflow, dbt, Git, Docker, Terraform, Grafana, Prometheus
Responsibilities
Develop and operate scalable ETL/ELT data pipelines; Integrate data from diverse sources (databases, APIs, files, cloud); Build and evolve data warehouse/lake/lakehouse architectures; Transform, clean, and validate large datasets; Ensure data quality, consistency, and availability; Develop and optimize data models for reporting; Automate data processes and workflows; Monitor and optimize pipeline performance, stability, and costs; Implement monitoring, logging, and alerting solutions; Enforce data privacy, security, and governance requirements; Document data flows and technical solutions; Collaborate with data analysts and scientists to provide suitable data.
Seniority
Mid-Senior, hands-on IC
