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Brillio 25mo ago

AWS Data Specialist - R01558578

IndiaIndia·PuneEmployeemid
Data ScienceOtherData EngineeringData Specialist
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Quick Summary

Overview

Lead Data Engineer Job Title: Data Product Engineer Experience: 5+ YearsLocation: 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…

Key Responsibilities

Collaborate with cross-functional teams to design, build, maintain, and monitor high-quality Data Products that meet diverse customer and business requirements.

Technical Tools
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Lead Data Engineer

    • Experience: 5+ Years
    Location: India (Hybrid / Remote as applicable)

    Experience: 5+ Years
    Location: India (Hybrid / Remote as applicable)

    Experience: 5+ Years
    Location: India (Hybrid / Remote as applicable)

    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.

    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.

    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.

    Responsibilities

    ~3 min read
  • →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.
  • →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.
  • →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.
  • Data pipelines, ETL / ELT processes
  • Data modeling and analytics
  • Data exploration and visualization
  • Data pipelines, ETL / ELT processes
  • Data modeling and analytics
  • Data exploration and visualization
  • Data pipelines, ETL / ELT processes
  • Data modeling and analytics
  • Data exploration and visualization
  • AWS (strong hands-on experience):
  • S3, Redshift, Athena, Lambda, Glue
  • CodePipeline, CloudFormation
  • SNS
  • Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  • AWS (strong hands-on experience):
  • S3, Redshift, Athena, Lambda, Glue
  • CodePipeline, CloudFormation
  • SNS
  • Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  • AWS (strong hands-on experience):
  • S3, Redshift, Athena, Lambda, Glue
  • CodePipeline, CloudFormation
  • SNS
  • Working knowledge of: Microsoft Azure and Google Cloud Platform (GCP)
  • SSIS
  • Databricks
  • Spark
  • SQL
  • Python
  • R, Scala (good to have)
  • SSIS
  • Databricks
  • Spark
  • SQL
  • Python
  • R, Scala (good to have)
  • SSIS
  • Databricks
  • Spark
  • SQL
  • Python
  • R, Scala (good to have)
  • SQL Server
  • DynamoDB
  • ArangoDB
  • SQL Server
  • DynamoDB
  • ArangoDB
  • SQL Server
  • DynamoDB
  • ArangoDB
  • JSON, XML
  • Parquet, CSV
  • JSON, XML
  • Parquet, CSV
  • JSON, XML
  • Parquet, CSV
  • Amazon QuickSight
  • Tableau
  • Microsoft Excel
  • Amazon QuickSight
  • Tableau
  • Microsoft Excel
  • Amazon QuickSight
  • Tableau
  • Microsoft Excel
  • Miro
  • Confluence
  • Miro
  • Confluence
  • Miro
  • Confluence
  • 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
  • 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
  • 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

    • Location & Eligibility

    Where is the job
    Pune, India
    Hybrid — some on-site time required
    Who can apply
    IN
    Listed under
    India

    Listing Details

    Posted
    December 11, 2025
    First seen
    March 26, 2026
    Last seen
    June 5, 2026

    Posting Health

    Days active
    71
    Repost count
    0
    Trust Level
    25%
    Scored at
    June 6, 2026

    Signal breakdown

    freshnesssource trustcontent trustemployer trust
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