Job Title

Data Engineer – AWS Data PlatformJob SummaryWe are looking for a highly skilled and motivated Data Engineer with strong expertise in AWS data services to join our data platform team. The ideal candidate will have hands-on experience designing scalable data pipelines, workflow orchestration frameworks, and large-scale data migration solutions.This role will be responsible for building robust cloud-native data engineering solutions on AWS, migrating datasets from legacy systems and data warehouses, and ensuring secure and efficient data processing pipelines across distributed environments.Key ResponsibilitiesAWS Data Pipeline DevelopmentDesign and implement scalable ETL/ELT data pipelines using AWS Glue, AWS Lambda, and AWS S3.Build and maintain high-performance data ingestion frameworks for processing large-scale datasets.Implement data pipelines for data warehousing and analytics platforms such as AWS Redshift.Optimize storage and querying strategies using AWS S3 data lakes.Data Workflow OrchestrationDevelop and maintain data workflow orchestration frameworks using tools such as Apache Airflow or AWS Step Functions.Automate complex workflows including data ingestion, transformation, validation, and loading processes.Build reusable and configurable workflows to support multiple data processing use cases.Data Migration & IntegrationLead data migrations from legacy data warehouse technologies to modern AWS data platforms.Perform data migration from RDBMS systems (e.g., MySQL, SQL Server, Oracle) to AWS S3 or AWS Redshift.Design scalable migration frameworks for large datasets with minimal downtime.Integrate data sources from enterprise applications and external systems.Data Security & GovernanceImplement secure data pipelines using AWS security best practices.Manage access control and data governance using AWS IAM and Lake Formation.Ensure data encryption, access management, and compliance across all data platforms.Performance Optimization & MonitoringMonitor data pipelines and troubleshoot performance issues.Optimize ETL workflows for scalability, reliability, and cost efficiency.Implement logging, monitoring, and alerting mechanisms for data pipelines.Required Skills & Qualifications (Must Have)5+ years of experience in Data Engineering or Data Platform developmentStrong hands-on experience with:AWSAWS GlueAWS S3AWS LambdaExperience with Data Workflow Orchestration tools such as Apache Airflow or AWS Step FunctionsExperience performing data migrations from other data warehouse technologiesExperience performing data migrations from RDBMS systems to AWS S3 or AWS RedshiftStrong expertise in Python and SQL for building scalable data pipelinesSolid understanding of ETL/ELT concepts, data partitioning, and distributed data processingExperience working with version control systems such as GitLab or BitbucketStrong debugging, analytical thinking, and problem-solving skillsBasic understanding of Object-Oriented Programming conceptsIndustry Knowledge & ExperienceExperience building cloud-native data engineering solutions on AWSExperience with data warehouse architectures and large-scale analytics platformsHands-on experience with data extraction, transformation, and migration frameworksExperience working in high-volume data environments such as FinTech, analytics platforms, or enterprise data systemsGood to Have SkillsIBM CognosAWS AthenaAWS Lake FormationAWS RedshiftAWS Glue Data CatalogAWS SageMakerAWS IAMSoft SkillsStrong communication skills to present technical solutions and recommendations to stakeholdersAbility to work cross-functionally in a fast-paced and evolving environmentDetail-oriented with a proactive approach to identifying and solving data platform challengesAbility to collaborate effectively with data scientists, analysts, and platform engineering teams