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Tech Stack
Tools & technologiesAmazon RedshiftAWSCloudDynamoDBElasticSearchETLKafkaPythonShell ScriptingSparkSQLTerraform
About the role
Key responsibilities & impact- Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.
- Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
- Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.
- Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.
- Participate in the architecture and system design discussions for high-scale data engineering projects.
- Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices.
- Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.
- Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.
- Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
- Architect and implement CI/CD strategies for enterprise data platforms.
- Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle.
- Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.
- Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.
Requirements
What you’ll need- Required Qualifications:
- - Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
- - 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
- - Strong programming experience with Python, Shell scripting, and SQL.
- - Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.
- - Experience in serverless application development and data pipeline orchestration.
- - Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.
- - Knowledge of ETL/ELT, data modeling, and big data technologies.
- - Familiarity with data warehousing concepts and cloud-based architecture.
- - Strong problem-solving skills and attention to detail.
- - Excellent communication and teamwork abilities.
- Preferred Qualifications:
- - Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
- - Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation).
- - Experience with DevOps practices and CI/CD pipelines.
- - Experience implementing end-to-end streaming solutions (Amazon Kinesis, SQS, Kafka).
- - AWS Solutions Architect or AWS Developer Certification preferred.
- - Understanding of Lakehouse/data cloud architecture.
- - Knowledge of data governance and compliance standards.
Benefits
Comp & perks- For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonSQLShell ScriptingETL/ELTData ModelingBig Data TechnologiesData Ingestion PipelinesData WarehousingServerless Application DevelopmentStreaming Solutions
Soft Skills
Problem-SolvingAttention to DetailCommunicationTeamwork
Certifications
AWS Solutions Architect CertificationAWS Developer Certification
