Data Engineer

What You’ll Do

• Data Pipeline & Architecture: Build, maintain, and troubleshoot moderately complex data pipelines (using Airflow) to ingest, transform, and aggregate data from disparate sources.
• Data Quality & Modeling: Design and implement data models, optimize performance, and develop rules/tracking processes to support data quality models based on data characteristics.
• Analysis & Interpretation: Perform design, creation, and deep-dive interpretation of large, highly complex datasets.
• Agile Project Delivery: Organize workflows, manage time effectively, and complete tasks accurately within budget and on time in a rapid development environment.
• Collaboration & Communication: Work independently under minimal supervision while maintaining effective, clear communication with peers, project leads, and management.
  

What Experience You Need

• 3+ years of hands-on experience in software or data engineering with strong proficiency in Python and SQL.
• 2+ years of experience working with enterprise relational databases and cloud warehouses (e.g., PostgreSQL, MySQL, BigQuery).
• Practical experience building and orchestrating ETL/ELT pipelines using workflow management tools like Apache Airflow.
• Hands-on experience developing within a Google Cloud Platform (GCP) environment (Cloud Storage, BigQuery).
• Demonstrated experience with version control (GitHub) and collaboration tools (Jira, Confluence).
• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
  

What Could Set You Apart

• Hands-on experience managing directed acyclic graphs (DAGs) in Google Cloud Composer.
• Prior exposure to modern enterprise data platforms such as Snowflake or Databricks.
• Understanding of streaming data frameworks (e.g., Apache Pub/Sub, Kafka) and CI/CD deployment pipelines.