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
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