AWS Data Specialist - R01558578

Lead Data Engineer

Primary Skills

• Job Title: Data Product Engineer
  
  

Experience: 5+ Years

Location: India (Hybrid / Remote as applicable)

Job Summary

We are looking for an experienced Data Product Engineer with a strong background in building, delivering, and supporting data-driven products for both operational and analytical use cases. The ideal candidate will combine product thinking with deep data engineering expertise to transform raw data into scalable, secure, and production-ready data products that integrate seamlessly into modern digital ecosystems.

This role requires close collaboration with business stakeholders, strong software engineering practices, and a solid understanding of cloud-native data platforms.

Key Responsibilities

• Collaborate with cross-functional teams to design, build, maintain, and monitor high-quality Data Products that meet diverse customer and business requirements.
• Act as a subject matter expert (SME) by bridging technical and business perspectives to deliver meaningful, data-driven solutions.
• Manage the end-to-end data lifecycle, including data ingestion, transformation, storage, and provisioning for downstream consumers.
• Apply software engineering best practices—CI/CD, Git-based version control, Test-Driven Development (TDD), Definition of Done (DoD), and Agile methodologies—to data engineering workflows.
• Ensure data security, governance, and compliance standards are met across all data products.
• Develop and maintain clear documentation, promote knowledge sharing, and support onboarding for data products and platforms.
• Monitor data pipelines and products for reliability, performance, scalability, and cost efficiency.
• Integrate data products into broader digital and application ecosystems, supporting both real-time and batch use cases.
• Actively contribute to continuous improvement of data architecture, tooling, and processes.
  
  

Technical Skillset

Data Engineering & Analytics

• Data pipelines, ETL / ELT processes
• Data modeling and analytics
• Data exploration and visualization
  
  

Cloud Platforms

• AWS (strong hands-on experience):
• S3, Redshift, Athena, Lambda, Glue
• CodePipeline, CloudFormation
• SNS
• Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  
  

Data Tools & Frameworks

• SSIS
• Databricks
• Spark
• SQL
• Python
• R, Scala (good to have)
  
  

Databases

• SQL Server
• DynamoDB
• ArangoDB
  
  

Data Formats

• JSON, XML
• Parquet, CSV
  
  

Visualization & Exploration Tools

• Amazon QuickSight
• Tableau
• Microsoft Excel
  
  

Collaboration & Documentation

• Miro
• Confluence
  
  

Core Competencies

• Strong product mindset with a customer-centric approach to data solutions
• Excellent planning, communication, and organizational skills
• Proficiency with Git / GitHub and version control best practices
• Experience with CLI scripting (Bash, PowerShell, AWS CLI)
• Agile mindset with exposure to Test-Driven Development (TDD)
• Familiarity with modern data management concepts, including Data Mesh and Event-Driven / Streaming architectures
  
  

t

Specialization

• Job Title: Data Product Engineer
  
  

Experience: 5+ Years

Location: India (Hybrid / Remote as applicable)

Job Summary

We are looking for an experienced Data Product Engineer with a strong background in building, delivering, and supporting data-driven products for both operational and analytical use cases. The ideal candidate will combine product thinking with deep data engineering expertise to transform raw data into scalable, secure, and production-ready data products that integrate seamlessly into modern digital ecosystems.

This role requires close collaboration with business stakeholders, strong software engineering practices, and a solid understanding of cloud-native data platforms.

Key Responsibilities

• Collaborate with cross-functional teams to design, build, maintain, and monitor high-quality Data Products that meet diverse customer and business requirements.
• Act as a subject matter expert (SME) by bridging technical and business perspectives to deliver meaningful, data-driven solutions.
• Manage the end-to-end data lifecycle, including data ingestion, transformation, storage, and provisioning for downstream consumers.
• Apply software engineering best practices—CI/CD, Git-based version control, Test-Driven Development (TDD), Definition of Done (DoD), and Agile methodologies—to data engineering workflows.
• Ensure data security, governance, and compliance standards are met across all data products.
• Develop and maintain clear documentation, promote knowledge sharing, and support onboarding for data products and platforms.
• Monitor data pipelines and products for reliability, performance, scalability, and cost efficiency.
• Integrate data products into broader digital and application ecosystems, supporting both real-time and batch use cases.
• Actively contribute to continuous improvement of data architecture, tooling, and processes.
  
  

Technical Skillset

Data Engineering & Analytics

• Data pipelines, ETL / ELT processes
• Data modeling and analytics
• Data exploration and visualization
  
  

Cloud Platforms

• AWS (strong hands-on experience):
• S3, Redshift, Athena, Lambda, Glue
• CodePipeline, CloudFormation
• SNS
• Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  
  

Data Tools & Frameworks

• SSIS
• Databricks
• Spark
• SQL
• Python
• R, Scala (good to have)
  
  

Databases

• SQL Server
• DynamoDB
• ArangoDB
  
  

Data Formats

• JSON, XML
• Parquet, CSV
  
  

Visualization & Exploration Tools

• Amazon QuickSight
• Tableau
• Microsoft Excel
  
  

Collaboration & Documentation

• Miro
• Confluence
  
  

Core Competencies

• Strong product mindset with a customer-centric approach to data solutions
• Excellent planning, communication, and organizational skills
• Proficiency with Git / GitHub and version control best practices
• Experience with CLI scripting (Bash, PowerShell, AWS CLI)
• Agile mindset with exposure to Test-Driven Development (TDD)
• Familiarity with modern data management concepts, including Data Mesh and Event-Driven / Streaming architectures
  
  

Job requirements

Job Title: Data Product Engineer

Experience: 5+ Years

Location: India (Hybrid / Remote as applicable)

Job Summary

We are looking for an experienced Data Product Engineer with a strong background in building, delivering, and supporting data-driven products for both operational and analytical use cases. The ideal candidate will combine product thinking with deep data engineering expertise to transform raw data into scalable, secure, and production-ready data products that integrate seamlessly into modern digital ecosystems.

This role requires close collaboration with business stakeholders, strong software engineering practices, and a solid understanding of cloud-native data platforms.

Key Responsibilities

• Collaborate with cross-functional teams to design, build, maintain, and monitor high-quality Data Products that meet diverse customer and business requirements.
• Act as a subject matter expert (SME) by bridging technical and business perspectives to deliver meaningful, data-driven solutions.
• Manage the end-to-end data lifecycle, including data ingestion, transformation, storage, and provisioning for downstream consumers.
• Apply software engineering best practices—CI/CD, Git-based version control, Test-Driven Development (TDD), Definition of Done (DoD), and Agile methodologies—to data engineering workflows.
• Ensure data security, governance, and compliance standards are met across all data products.
• Develop and maintain clear documentation, promote knowledge sharing, and support onboarding for data products and platforms.
• Monitor data pipelines and products for reliability, performance, scalability, and cost efficiency.
• Integrate data products into broader digital and application ecosystems, supporting both real-time and batch use cases.
• Actively contribute to continuous improvement of data architecture, tooling, and processes.
  
  

Technical Skillset

Data Engineering & Analytics

• Data pipelines, ETL / ELT processes
• Data modeling and analytics
• Data exploration and visualization
  
  

Cloud Platforms

• AWS (strong hands-on experience):
• S3, Redshift, Athena, Lambda, Glue
• CodePipeline, CloudFormation
• SNS
• Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  
  

Data Tools & Frameworks

• SSIS
• Databricks
• Spark
• SQL
• Python
• R, Scala (good to have)
  
  

Databases

• SQL Server
• DynamoDB
• ArangoDB
  
  

Data Formats

• JSON, XML
• Parquet, CSV
  
  

Visualization & Exploration Tools

• Amazon QuickSight
• Tableau
• Microsoft Excel
  
  

Collaboration & Documentation

• Miro
• Confluence
  
  

Core Competencies

• Strong product mindset with a customer-centric approach to data solutions
• Excellent planning, communication, and organizational skills
• Proficiency with Git / GitHub and version control best practices
• Experience with CLI scripting (Bash, PowerShell, AWS CLI)
• Agile mindset with exposure to Test-Driven Development (TDD)
• Familiarity with modern data management concepts, including Data Mesh and Event-Driven / Streaming architectures