Data Engineer

• Design, build, and maintain scalable data pipelines (ETL/ELT)
• Develop and optimize data architecture, data lakes, and warehouses
• Ensure data quality, reliability, and integrity across systems
• Collaborate with Product, Engineering, and Analytics teams to define data needs
• Build real-time and batch data processing systems
• Optimize database performance and query efficiency
• Implement data governance, security, and best practices
• Mentor junior data engineers and promote engineering excellence

Requirements

• 5+ years of experience in data engineering or related roles
• Strong proficiency in Python and SQL — not just writing queries, but designing reusable, tested pipeline code
• Hands-on AWS experience (required): Redshift, S3, Athena, ECS, EventBridge
• Experience building and maintaining data warehouses — Redshift experience is a strong plus
• Familiarity with workflow orchestration tools such as Airflow or equivalent, including ECS-based scheduling patterns
• Experience with multi-database environments: PostgreSQL/Aurora and MySQL/MariaDB
• Strong understanding of data modeling, dimensional design, and schema evolution
• Experience with streaming technologies such as Kafka is a plus
• Comfort working in a fast-moving product company where priorities shift and pipelines must be resilient

Nice to Have

• Experience supporting machine learning pipelines
• Knowledge of data governance and privacy best practices
• Experience in fast-paced startups or product companies
• Exposure to BI tools (e.g., Metabase, Tableau, Power BI)