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