Cloud Data Engineer

Job Description

The Cloud Data Engineer is responsible for designing, building, and maintaining scalable, secure, and governed cloud-based data platforms. The role involves working with AWS, Databricks, and Informatica IDMC to support data ingestion, transformation, analytics, and reporting while ensuring data quality, security, and compliance.

The candidate will collaborate with cross-functional teams to deliver reliable data solutions that support healthcare analytics and digital transformation initiatives.

• Design and implement cloud-based data storage solutions including data lakes, data warehouses, and databases using AWS services such as Amazon S3, RDS, Redshift, and Dynamo
  
  DB, and Databricks Delta Lake.
• Develop, manage, and optimize data pipelines using AWS Glue, AWS Lambda, AWS Step Functions, Databricks, and Informatica IDMC.
• Integrate data from multiple internal and external sources while ensuring data quality, governance, and compliance.
• Build and maintain ETL/ELT processes using Databricks (Spark) and Informatica IDMC.
• Monitor and optimize data workflows and query performance to meet scalability and performance requirements.
• Implement data security controls, encryption, and compliance with data protection regulations.
• Automate data ingestion, transformation, and monitoring processes.
• Maintain documentation for data architecture, pipelines, and configurations.
• Collaborate with data scientists, analysts, and software engineers to deliver data solutions.
• Troubleshoot and resolve data-related issues to ensure data availability and integrity.
• Optimize cloud resource usage to control operational costs.

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• Minimum 8 years of relevant experience in data engineering.
• Hands‑on experience with AWS services, Databricks, and/or Informatica IDMC.
• Proficiency in Python, Java, or Scala.
• Strong knowledge of SQL and No
  
  SQL databases.
• Experience with data modeling, schema design, and complex data transformations.
• Strong analytical, problem‑solving, and communication skills.

• Experience with PySpark on Databricks.
• Knowledge of data governance and data cataloging tools, especially Informatica IDMC.
• Familiarity with Tableau or other data visualization tools.
• Experience with Docker and Kubernetes.
• Understanding of Dev Ops and CI/CD pipelines.
• Experience using Git or other version control systems.