ETL Developer - Bilingual
The ideal candidate should have strong experience in SQL, ETL development, and data transformation, along with exposure to modern AI-assisted development tools and automation practices. Experience working with US Healthcare data environments is highly preferred.
- Design, develop, test, and maintain ETL workflows and data pipelines.
- Integrate data from multiple on-prem and cloud-based systems.
- Develop and maintain data models, mappings, and data dictionaries.
- Monitor ETL jobs, troubleshoot failures, and resolve data quality issues.
- Collaborate with analysts, business teams, and stakeholders to understand integration requirements.
- Ensure data accuracy, consistency, completeness, and scalability across pipelines.
- Maintain technical documentation for ETL processes and data architecture.
- Implement best practices for ETL deployment, version control, and CI/CD.
- Utilize AI-assisted coding and automation tools to improve development efficiency and debugging.
- Support continuous improvements in data quality, performance, and operational reliability.
- Stay current with emerging ETL, cloud, and AI-driven data engineering technologies.
- Exposure to US Healthcare data standards such as HL7, FHIR, EDI 837/835, and claims processing.
- Understanding of HIPAA compliance and secure healthcare data handling practices.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- 3–5 years of hands-on ETL development experience.
- Strong experience with ETL tools such as Talend or SSIS.
- Strong SQL skills and experience with databases such as SQL Server, Oracle, MySQL, or Azure SQL.
- Experience with cloud and on-prem data environments.
- Familiarity with Git and CI/CD deployment practices.
- Experience using AI coding assistants or automation tools in development workflows.
- Strong analytical, troubleshooting, and problem-solving abilities.
- Excellent communication and collaboration skills.
- Ability to work independently in a fast-paced environment.
- Experience with Azure Data Factory, AWS Glue, Databricks, or similar cloud ETL platforms.
- Knowledge of Python or Spark for large-scale data transformations.
- Familiarity with data governance and metadata management tools.
- Exposure to AI/ML data pipelines or MLOps workflows.
- Healthcare domain experience is a plus.