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Job DescriptionDescription: Design and maintain enterprise-scale data pipelines using AWS cloud services, handling schema evolution in data feeds and delivering analytics-ready datasets to BI platforms. This role requires hands-on expertise with the full AWS data stack and proven ability to build enterprise-grade data solutions that scale. Requirements: Essential Functions • Build and orchestrate ETL/ELT workflows using Apache Airflow for complex data pipeline management, • Develop serverless data processing with AWS Lambda and EventBridge for real-time transformations, • Create scalable ETL jobs using AWS Glue with automated schema discovery and catalog management, • Execute database migrations and continuous replication using AWS DMS, • Design and optimize Amazon Redshift data warehouses and Amazon Athena federated queries, • Implement streaming data pipelines with Apache Kafka for real-time ingestion, • Manage schema changes in data feeds with automated detection and pipeline adaptation No supervisory responsibilities Required Skills/Abilities • Airflow: DAG development, custom operators, workflow orchestration, production deployment, • Lambda: Serverless functions, event triggers, performance optimization, • EventBridge: Event-driven architecture, rule configuration, cross-service integration, • Glue: ETL job development, crawlers, Data Catalog, schema management, • DMS: Database migrations, continuous replication, heterogeneous database integration, • Redshift: Cluster management, query optimization, workload management, • Develop and maintain data analogs, data cubes, queries, data visualization and reports, • Assist in testing code, governance, data quality, and documentation effort, • Reported data and visualizations and reports, • Collaborate with data stewards to test, clean, and standardize, • Evaluate patterns and meaningful insights from data through qualitative and quantitative analysis Data Technologies • Apache Kafka: Stream processing, topic design, producer/consumer development, • SQL: Advanced querying across multiple database platforms (PostgreSQL, MySQL, Oracle), • Python/Scala: Data processing, automation, custom pipeline development, • Schema Management: Automated detection, evolution strategies, backward compatibility, • Tableau: Data source optimization, extract management, connection configuration, • BusinessObjects: Universe design, report development, data feed creation, • 5+ years AWS data platform development, • 3+ years production Airflow experience with complex workflow orchestration, • Proven experience managing high-volume data feeds (TB+ daily) with schema evolution, • Database migration expertise using DMS for enterprise-scale projects, • BI integration experience with Tableau and BusinessObjects platforms, • Design fault-tolerant data pipelines with automated error handling and recovery, • Handle schema changes in real-time and batch data feeds without pipeline disruption, • Optimize performance across streaming and batch processing architectures, • Implement data quality validation and monitoring frameworks, • AWS Data Analytics Specialty or Solutions Architect Professional certification, • Experience with Infrastructure as Code (Terraform, CloudFormation), • Knowledge of DataOps practices and CI/CD for data pipelines Work is generally performed within an indoor office environment utilizing standard office equipment. General office environment requires frequent sitting; dexterity of hands and fingers to operate a computer keyboard and mouse; walking and standing for long periods of time; and lifting of less than 20 pounds.