Senior AWS Data Engineer

7 days ago

India Lean IT Inc. Full time
Company Description Lean IT Inc. is at the forefront of the technological revolution, with a proven track record of delivering state-of-the-art cloud solutions to a diverse clientele. As an official Salesforce Ridge Partner, we specialize in expert consultations, robust and customizable Salesforce solutions, and seamless API integrations. Our core competencies include Data Visualization, Big Data Implementation, Data Migration, and Data Modernization. This is a remote contract role for a Data Engineer (AWS, Power BI). The Data Engineer will be responsible for designing and implementing data models, managing data warehousing solutions, executing ETL processes, and conducting data analytics. This role will also involve data visualization tasks using Power BI, ensuring seamless data transitions and modernizing data infrastructures.

Title: Data Engineer (AWS, Power BI)
ASAP
Location: offshore / remote
Experience : 7 Yrs to 8 Yrs
 
Lead discovery of existing data pipelines and BI reporting tools and outputs. Document the existing data architecture and define the optimal to-be data warehouse configuration. Redefine schemas and build ETL pipelines to support integrated learning platforms. Consolidate services and toolsets to streamline the data ecosystem. Define and implement data privacy and access control governance controls across integrated systems. Implement data quality checks, maintain comprehensive documentation, and design API-based synchronization for ongoing data exchange between platforms. Ensure regulatory compliance throughout the integration process.

AWS
Power BI
Data Warehouse (AWS Redshift, Snowflake, Big-Query—though AWS preferred)
ETL / Data Pipelines
BI Reporting Tools
Data Engineering Skills
Data Architecture
Schema Redefinition / Data Modeling
ETL Design & Development
Data Consolidation & Integration
Data Quality Checks / Data Validation
Documentation (data lineage, pipeline documentation)
Data Privacy
Regulatory Compliance (GDPR, etc.)
Integrated Learning Platforms (LMS/LXP systems experience a plus)
Data Synchronization (API-based, automated exchange)
Discovery of Existing Data Pipelines
Designing Optimal Data Warehouse Configuration
Streamlining Data Ecosystem

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