AWS Quick sight

Job description

• Key Responsibilities
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• AWS QuickSight PixelPerfect Reporting
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• Design, develop, and deploy Pixel Perfect reports and interactive dashboards using AWS QuickSight.
• Ensure accurate, visually appealing, and business relevant reporting for stakeholders.
• Customize and optimize QuickSight reports with advanced features like calculated fields, filters, and visualizations to meet business needs.
• Data Engineering and Data Integration
• Develop and maintain scalable data pipelines using Google Cloud BigQuery, DataProc, DataFlow, and DataFusion.
• Design and implement ETL processes to extract, transform, and load data from various sources into data lakes and warehouses.
• Integrate data from on premise systems and other cloud platforms (AWS, GCP) into BigQuery and other data storage solutions.
• BigQuery
• Develop and manage BigQuery queries and data models to support reporting, analytics, and machine learning workloads.
• Work with large datasets, ensuring high performance and cost efficiency in data processing and querying.
• Leverage BigQuery ML and other BigQuery features for advanced analytics and reporting.
• DataFlow, DataProc, and DataFusion
• Build and manage cloud native data pipelines using DataFlow and DataProc for stream and batch processing.
• Design, implement, and maintain data transformations using DataFusion to integrate and manage diverse datasets from different sources.
• Leverage cloud based tools for automating data workflows and ensuring data consistency across systems.
• Collaboration with Business Teams
• Collaborate with business analysts, product owners, and data scientists to understand data requirements and translate them into actionable insights and reports.
• Provide training and support to business users on using AWS QuickSight for self-service analytics.
• Data Security and Governance
• Ensure that all data processing and reporting comply with security and governance policies.
• Manage permissions, roles, and data access controls in AWS and Google Cloud environments.
• Implement and maintain data quality checks and monitoring for all data pipelines.
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• GCP Data Services
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• Experience with DataProc, DataFlow, and DataFusion for managing and processing big data in the cloud.
• Strong knowledge of Google Cloud Platform tools for data engineering and integration.
• ETL Development Strong background in ETL development using cloudnative technologies like DataFlow, DataProc, and other data integration tools.
• SQL & Data Modeling Advanced SQL skills for querying and optimizing large datasets in BigQuery and other relational databases.
• Business Intelligence Hands on experience with creating dashboards, reports, and visualizations in AWS QuickSight or similar BI tools Tableau, Power BI
• Cloud Infrastructure Familiarity with AWS and GCP cloud environments, data storage, and orchestration services Google Cloud Storage, AWS S3
• Data Pipeline Automation Experience automating data pipelines, error handling, and monitoring for end to end data flow.
• Data Governance Knowledge of data governance principles, data security, and ensuring compliance in cloud based data engineering.
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• Preferred Skills
• Experience with AWS Glue or Google Cloud Dataflow for ETL processing.
• Familiarity with Python, Java, or Scala for writing custom data processing logic.
• Knowledge of Machine Learning concepts and tools BigQuery ML, TensorFlow for integrating analytics into data pipelines.
• Familiarity with Airflow or similar orchestration tools.