About the RoleWe are seeking an experiencedAWS Data Engineerwith 4+ years of experience to design, develop, and maintain scalable data pipelines and transformation frameworks using AWS native tools and modern data engineering technologies.
The ideal candidate will have a strong grasp oflarge, complex, and multi-dimensional datasets, hands-on expertise inAWS Data Engineering services, and deep understanding ofdata modeling and performance optimization.
Exposure toVeeva API integrationwill be considered an added advantage.
Key Responsibilities- Design, develop, and optimizedata ingestion, transformation, and storage pipelineson AWS.
- Manage and processlarge-scale structured, semi-structured, and unstructured datasetsefficiently.
- Build and maintainETL/ELT workflowsusing AWS native tools such asGlue, Lambda, EMR, and Step Functions.
- Design and implementscalable data architecturesleveragingPython, PySpark, and Apache Spark.
- Develop and maintaindata modelsaligned with business and analytical requirements.
- Collaborate closely withdata scientists, analysts, and business stakeholdersto ensure data availability, reliability, and quality.
- Handleon-premises and cloud data warehouse systems, ensuring optimal performance and smooth migration strategies.
- Maintain awareness ofemerging trends and best practicesin data engineering, analytics, and cloud computing.
Required Skills & Experience- Proven hands-on experience withAWS Data Engineering stack, including:
- AWS Glue, S3, Redshift, EMR, Lambda, Step Functions, Kinesis, Athena, and IAM.
- Proficiency inPython, PySpark, and Apache Sparkfor data transformation and processing.
- Strong understanding ofdata modeling principles(conceptual, logical, and physical).
- Experience working withmodern data platformssuch asSnowflake, Dataiku, or Alteryx(good to have, not mandatory).
- Familiarity withon-premise and cloud data warehousesandmigration strategies.
- Solid knowledge ofETL design patterns, data governance, and data quality/security best practices.
- Understanding ofDevOps for Data Engineering, includingCI/CD pipelinesandInfrastructure as Code (IaC)usingTerraform or CloudFormation(good to have).
- Excellentproblem-solving, analytical, and communication skills.
Qualifications- Bachelor's or Master's degree inComputer Science, Information Technology, Data Engineering, or a related field.
- Minimum4 years of experienceindata engineeringwith a focus onAWStools and ecosystem.
- Continual learning mindset with interest inemerging technologies and cloud data innovations.
