Data Engineer

About The Role

The role owns the design, implementation, and scaling of core data infrastructure and high-throughput pipelines that power analytical models and operational reporting.

The data team works closely with product and analytics groups to ensure data freshness, accuracy, and reliability across modern cloud data warehouses.

Key Responsibilities

• Architect, build, and maintain robust ETL/ELT data pipelines using Python, SQL, and modern orchestration tools like Airflow or Prefect

• Model scalable data structures and dimensional schemas within cloud data warehouses such as Snowflake, BigQuery, or Redshift

• Monitor data pipeline performance, optimize heavy queries, and troubleshoot data quality anomalies using automated testing frameworks

• Collaborate with analytics and engineering teams to define data governance policies, metadata management, and lineage tracking

• Write clean, version-controlled code, participate in architectural reviews, and contribute to internal data engineering standards

What We Are Looking For

• 3–6 years of professional experience in data engineering, backend development, or analytics engineering

• Advanced SQL and Python programming skills for data transformation and pipeline automation

• Demonstrated experience with orchestrating tools like Apache Airflow, Dagster, or Prefect in production environments

• Hands-on experience with cloud data warehouses (Snowflake, BigQuery, AWS Redshift) and data modeling methodologies (Kimball)

• BS or MS in Computer Science, Statistics, Engineering, or equivalent practical experience

• Bonus: Experience with streaming architectures (Kafka, Flink) and Infrastructure-as-Code tools (Terraform)