Data Engineer
Summary
Build and maintain AWS and Databricks data pipelines to support global supply-chain analytics, using PySpark, Glue, Lambda, S3, and Redshift.
Fixed-term employment: 6 months
Shift and work management: hybrid, 3 days onsite
As a Data Engineer, you will be responsible for building and maintaining scalable data pipelines and infrastructure using AWS and Databricks. You'll work closely with data scientists, analysts, and business stakeholders to enable data-driven decision-making across company's global supply chain.
Key Responsibilities
- Develop and optimize data pipelines usingDatabricks (PySpark)andAWS services(Glue, Lambda, S3, Redshift, etc.)
- Implement data ingestion, transformation, and integration workflows
- Ensure data quality, reliability, and performance across systems
- Collaborate with cross-functional teams to understand data requirements and build analytical data layer for analytics consumption
- Monitor and troubleshoot data workflows and infrastructure
- Maintain documentation and support CI/CD practices for data engineering
Qualifications
- Bachelor's degree in Computer Science, Engineering, or related field
- 3+ years of experience in data engineering withAWSandDatabricks
- Strong skills inPython,SQL, andPySpark
- Experience withdata lakehouse architectures,Delta Lake, andETL frameworks
- Familiarity with DevOps tools and Infrastructure as Code (e.g., Terraform)