AWS Data Engineer
New
T
Tech HoldingCloud Data Consulting
India, RemoteContractSenior
Salary not disclosed
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Job Details
- Experience
- 5+ Years
- Required Skills
- AWSPythonSQLSparkCI/CD
Requirements
- 5+ years of experience in Data Engineering.
- Strong programming skills in Python and SQL.
- Hands-on experience with Apache Spark / PySpark.
- Extensive experience with AWS data services including Glue, S3, Redshift, Athena, Lambda, Step Functions, EventBridge, and IAM.
- Experience designing and implementing ETL/ELT pipelines.
- Strong knowledge of data modeling, data warehousing, and data lake architecture.
- Experience with Apache Airflow or Amazon MWAA.
- Strong understanding of Data Governance, Metadata Management, Business Glossary, and Data Lineage.
- Experience implementing Data Quality, Audit Logging, and Data Reconciliation frameworks.
- Experience with Amazon QuickSight, semantic datasets, and BI reporting.
- Experience with Git, CI/CD, and Infrastructure as Code (Terraform or CloudFormation).
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL/ELT workflows on AWS.
- Modernize legacy data platforms by migrating Apache Airflow/MWAA workloads to AWS-native orchestration services.
- Migrate and optimize Amazon EMR workloads to AWS Glue.
- Design and implement scalable data lake and data warehouse solutions using AWS services.
- Develop robust data models, semantic layers, and standardized KPI definitions to support business analytics.
- Build and maintain data quality, validation, anomaly detection, and monitoring frameworks.
- Implement metadata management, data lineage, and data governance best practices.
- Develop automated deployment pipelines and infrastructure using Infrastructure as Code (IaC).
- Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
- Collaborate with business stakeholders to understand reporting requirements and translate them into scalable data solutions.
- Support QuickSight semantic datasets, dashboard optimization, and Power BI migration initiatives.
- Participate in UAT, production deployments, knowledge transfer, and post-production support.
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