Data Engineer (Hybrid)

About the role

This Data Engineer position is focused on building and maintaining reliable data pipelines, processing and integrating data from multiple sources into data warehouses or data lakes, and ensuring data quality and consistency across systems.

Key Responsibilities

• Build and maintain reliable ETL/ELT pipelines
• Process and integrate data from multiple sources into data warehouses or data lakes
• Write efficient and maintainable SQL queries
• Ensure data quality, consistency, and validity across data pipelines
• Collaborate with Data Analysts, Data Scientists, Product, and Engineering teams
• Monitor, troubleshoot, and optimize pipeline performance.

Requirements

• 3–5 years of experience as a Data Engineer or in a similar role
• Strong SQL skills and a solid understanding of basic data modeling
• Hands-on experience using Python for data processing
• Experience with ETL/ELT tools or workflow orchestration platforms such as Airflow, dbt, Dagster, or similar tools
• Familiarity with data warehouses such as BigQuery, Snowflake, Redshift, or PostgreSQL
• Understanding of data quality, partitioning, indexing, and pipeline monitoring.

Nice to Have

• Experience with cloud platforms such as GCP, AWS, or Azure
• Familiarity with Apache Spark, Apache Kafka, or data streaming
• Experience working with analytics teams or production data platforms.