Data Engineer
Core
Design, build, and maintain scalable data pipelines and ETL/ELT workflows to integrate data from multiple sources into data warehouses or lakes for clients.
Role type
Mid-level Data Engineer
Builds
Scalable data pipelines, ETL/ELT workflows, data warehouses, and data lakes
Domain
Data Engineering / Cloud Platforms
Deliverable
production ML models | product features | dashboards & analysis | infrastructure
Required skills
SQL, Python/Java/Scala, ETL/ELT pipeline development, Airflow/Azure Data Factory/Databricks, data modeling, schema design, relational and NoSQL database management, cloud platforms (Azure/AWS/GCP), big data frameworks (Spark/Hadoop/Kafka), data quality validation, CI/CD, Git
Preferred skills
Data governance, security, compliance initiatives, troubleshooting data workflows, documentation of data processes and architectures
Technologies
Airflow, Azure Data Factory, Databricks, Spark, Hadoop, Kafka, Azure, AWS, GCP
Responsibilities
Design and build scalable data pipelines; Develop and optimize ETL/ELT workflows; Ensure data quality and integrity through validation and monitoring; Implement and manage data storage solutions; Monitor and troubleshoot data workflows; Support data governance, security, and compliance initiatives; Document data processes, architectures, and best practices
Seniority
Mid-level, hands-on IC
