Data Engineer (Hybrid)

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.

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