Data Engineer
Summary
Designs and maintains data pipelines, warehouses, and lakes, ensuring data quality and performance while collaborating with analysts and engineers.
- Design, build, and manage data pipelines (ETL/ELT) from various data sources
- Build and maintain data warehouses/data lakes
- Ensure data quality, consistency, and reliability (data quality & governance)
- Optimize query performance and data processes for efficiency and scalability
- Collaborate with Data Analysts, Data Scientists, and Product/Engineering teams to understand data requirements
- Monitor, troubleshoot, and maintain existing data systemsImplement best practices in data security and compliance
- Document data architecture, pipelines, and workflowsAutomate data processes to reduce manual work
- Bachelor's degree in Computer Science, Information Systems, Informatics Engineering, or related field
- Minimum 2-3 years of experience as a Data Engineer or similar role
- Advanced proficiency in SQL
- Strong programming skills in Python, Scala, or JavaExperience with ETL/ELT tools (Airflow, dbt, Talend, NiFi, etc.)
- Familiarity with the Big Data ecosystem (Hadoop, Spark, Kafka)
- Experience with cloud platforms (AWS, GCP, or Azure) — particularly data services like BigQuery, Redshift, S3, or Snowflake
- Solid understanding of data modeling, data warehousing, and databases (relational & NoSQL)
- Familiarity with version control (Git) and CI/CD practices