Technical Lead Big Data Engineer (AWS)
- 5+ years of experience in Big Data or Data Engineering, including supporting production data platforms
- Strong proficiency in Python, PySpark, and Apache Spark for large-scale data processing
- Hands-on experience with AWS data services such as Glue, S3, Athena, Aurora PostgreSQL, and Lambda
- Experience with Apache Airflow for data pipeline orchestration and scheduling
- Strong knowledge of SQL, data ingestion, ETL processes, and data quality practices
- Experience with Docker, Terraform, and CI/CD pipelines using GitHub Actions or similar tools
- Familiarity with Python development and testing tools such as pytest, Pydantic, ruff, or mypy
- Understanding of healthcare data regulations such as HIPAA/HITRUST, multi-tenant architectures, or data retention requirements is a plus
- Readiness to travel to the United States for a three-month business trip in Q1 2027
- Upper-intermediate or higher level of English, with strong communication and problem-solving skills
- Support, maintain, and enhance an existing AWS-based data platform and data ingestion pipelines
- Develop and optimize data processing workflows using Python, PySpark, Apache Spark, and AWS Glue
- Monitor and troubleshoot data pipelines, ensuring reliability, performance, and data quality
- Work with AWS services such as S3, Aurora PostgreSQL, Athena, Lambda, SQS, SNS, and EventBridge
- Maintain and improve workflow orchestration using Apache Airflow
- Support infrastructure and deployment processes using Docker, Terraform, and Amazon EKS
- Apply software engineering best practices, including automated testing, code quality checks, and CI/CD processes
- Utilize AI-assisted development tools such as Claude Code to support implementation, testing, and code reviews
- Collaborate with remote engineering teams to resolve technical issues, implement improvements, and ensure platform stability
- Support data security, governance, and compliance practices within a regulated healthcare environment
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