Data Engineer

Summary

With over 14 years of progressive experience in data engineering, Ive led the design and implementation of large-scale, cloud-native data platforms that power real-time analytics, data warehousing, and business intelligence at enterprise scale. Currently serving as a Data Engineer at Amazon, I specialize in building high-performance ETL/ELT pipelines on AWS, driving significant gains in latency reduction, automation, and system observability.

My career spans leadership roles across Amazon, Genpact, and TCS, where Ive consistently delivered measurable impactmigrating 12TB+ datasets to Snowflake, optimizing billion-record pipelines with PySpark, and cutting infrastructure and support costs by up to 80% through modernization initiatives. My technical strengths include AWS Glue, Snowflake, Azure Data Factory, and data modeling techniques that align deeply with business goals.

From transforming legacy systems into near-real-time ELT architectures to automating data quality and governance frameworks, my focus is on enabling secure, scalable, and high-value data ecosystems. I bring a unique mix of deep technical acumen, process efficiency, and collaborative problem-solving that positions data as a strategic driver across organizations.

Expectations

In my next role, Im looking for more than just a list of tasks Im hoping to find meaningful challenges that match my experience and allow me to keep growing. I want to contribute to projects where I can design scalable solutions, lead key initiatives, and work with others who care deeply about building great data systems.

Recognition and team support matter to me. Ive learned that feeling valued goes a long way, and Im eager to be part of a culture where contributions are noticed and collaboration is encouraged. I also place a strong emphasis on work-life balance and flexibility having the space to do focused work, while still being able to show up for life outside of work.

Ultimately, I want to join a company that sees data as a strategic asset and empowers its engineers to innovate, take ownership, and make a real impact.

Employment Preferences

Expected Base Salary

**0,000 USD

Academic Degree

Experience

Skills

• Tools
• SQL
• PL-SQL
• Python
• TypeScript
• Spark
• PySpark
• Hive
• Pandas
• NumPy
• Sqoop
• AWS Glue
• Azure Data Factory
• Databricks
• AWS DMS
• Kinesis
• Qlik Replicate
• HVR
• Redshift
• Snowflake
• Greenplum
• Oracle
• PostgreSQL
• Aurora
• MS-SQL Server
• MongoDB
• HBase
• DynamoDB
• AWS CLI
• AWS Lambda
• AWS IAM
• CloudWatch
• QuickSight
• Power BI
• ELT
• ETL
• CDC
• Change Data Capture
• Data Modeling
• SCD
• Slowly Changing Dimensions
• Time Travel
• Streams
• Dimensional Modeling
• Data Warehouse
• Data Migration
• Data Quality
• Batch Processing
• Real-time Data Processing
• Concepts
• Methodologies
• Big Data Technologies
• Cloud Platforms
• AWS
• Azure
• Metadata-driven Frameworks
• Data Integration
• Data Pipeline Automation
• Data Governance
• Performance Optimization
• Cost Reduction
• Infrastructure Optimization
• Conformed Dimensions
• Regulatory Compliance
• Agile SDLC
• DevOps For Data
• BI
• Reporting Solutions
• Certifications
• Standards
• SnowPro Core
• Lean Six Sigma
• Roles
• Responsibilities
• Functional Keywords
• Senior Data Engineer
• Technical Architect
• Data Engineer
• Modeler
• Data Platform Modernization
• Cross-functional Collaboration
• Operational Monitoring
• Architecture Planning
• Legacy System Migration