Data Engineer (m/w/d)
Core
Building, developing, and operating modern data platforms and pipelines to integrate, process, and store data from diverse sources 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 | product features | dashboards & analysis
Required skills
SQL, Python, relational database modeling, ETL/ELT processes, Data Warehouse/Lake concepts, Git, Cloud fundamentals
Preferred skills
AWS/Azure/GCP, Databricks/Snowflake/Fabric, Apache Spark, Apache Airflow, Docker/Kubernetes, Infrastructure as Code (Terraform), CI/CD, Streaming (Kafka), Data Governance
Technologies
Python, SQL, Azure, AWS, Google Cloud, Databricks, Snowflake, Microsoft Fabric, PostgreSQL, SQL Server, Oracle, Apache Spark, Airflow, dbt, Git, Docker, Terraform, Grafana, Prometheus
Responsibilities
Develop and operate scalable ETL/ELT pipelines; Integrate data from databases, APIs, files, and cloud systems; 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 Data Scientists to provide suitable data
Seniority
Mid-Senior, hands-on IC
