Key Responsibilities
- Design, build, and optimize scalable data pipelines to support real-time and batch processing
- Develop and maintain data models, schemas, and warehouses for analytical and operational use cases
- Collaborate with cross-functional teams to define data requirements and deliver high-quality datasets
- Implement data governance, quality checks, and monitoring to ensure reliability and accuracy
- Optimize query performance and storage solutions for large-scale datasets
- Mentor junior engineers and contribute to best practices in data engineering
Requirements
- 5+ years of experience in data engineering or related fields
- Proficiency in Python, SQL, and data pipeline tools (e.g., Airflow, Spark)
- Experience with data warehousing solutions (e.g., Snowflake, BigQuery, Redshift)
- Knowledge of cloud platforms (AWS, GCP, or Azure) and big data technologies
- Strong problem-solving skills and ability to work in fast-paced environments