Data ScienceOtherData EngineeringData SpecialistAws Data Specialist
Lead Data Engineer
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.
Responsibilities
~1 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.
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)
SSIS
Databricks
Spark
SQL
Python
R, Scala (good to have)
SQL Server
DynamoDB
ArangoDB
JSON, XML
Parquet, CSV
Amazon QuickSight
Tableau
Microsoft Excel
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
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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.
Responsibilities
~1 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.
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)
SSIS
Databricks
Spark
SQL
Python
R, Scala (good to have)
SQL Server
DynamoDB
ArangoDB
JSON, XML
Parquet, CSV
Amazon QuickSight
Tableau
Microsoft Excel
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
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.
Responsibilities
~1 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.
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)
SSIS
Databricks
Spark
SQL
Python
R, Scala (good to have)
SQL Server
DynamoDB
ArangoDB
JSON, XML
Parquet, CSV
Amazon QuickSight
Tableau
Microsoft Excel
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
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