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What you’ll work on

Full posting

Design and architect scalable AWS data pipelines and solutions
Develop and optimize ETL processes using EMR, Redshift, Athena and DMS
Configure real-time data streaming and ingestion with Kinesis and API Gateway
Lead implementation and integration of Stibo MDM solutions
Lead technical reviews and mentor junior engineers

From the employer’s posting

Design and architect scalable data pipelines and solutions using AWS native services

Develop, implement, and optimize ETL processes leveraging AWS technologies such as EMR, Redshift, Athena, and DMS

Configure and manage real-time data streaming and ingestion frameworks utilizing Kinesis and Amazon API Gateway

Lead the implementation and integration of Master Data Management (MDM) solutions using Stibo within enterprise data platforms

Lead technical reviews, mentor junior engineers, and drive adoption of emerging data technologies within the organization

What you’ll bring

All qualifications

Core experience

Expertise in designing and managing data pipelines and ETL workflows on AWS
Strong experience with Spark using Scala for large-scale data processing
Hands-on experience with Oozie workflow scheduling and orchestration
Deep knowledge of real-time data streaming with AWS Kinesis
Proven ability to configure and optimize Amazon Redshift for analytics workloads
Experience with DynamoDB for NoSQL database solutions

Preferred experience

Experience integrating AWS data solutions with third-party analytics and visualization tools
Familiarity with advanced data governance and data quality frameworks in MDM environments
Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline
Proficiency in optimizing performance for large-scale distributed data systems

Qualification wording

Expertise in designing and managing data pipelines and ETL workflows on AWS

Strong experience with Spark using Scala for large-scale data processing

Hands-on experience with Oozie workflow scheduling and orchestration

Deep knowledge of real-time data streaming with AWS Kinesis

Proven ability to configure and optimize Amazon Redshift for analytics workloads

Experience with DynamoDB for NoSQL database solutions

Experience integrating AWS data solutions with third-party analytics and visualization tools

Familiarity with advanced data governance and data quality frameworks in MDM environments

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline

Proficiency in optimizing performance for large-scale distributed data systems

Education & alternatives

Desired Qualifications: - Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline - AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional

Tools in this posting

Scala
AWS
Dynamodb
NoSQL
Redshift
Spark

Source

- Expertise in designing and managing data pipelines and ETL workflows on AWS - Strong experience with Spark using Scala for large-scale data processing - Hands-on experience with Oozie workflow scheduling and orchestration

Job requirements Experience Range: 7 to 10 years of experience in advanced AWS data engineering, including significant expertise in Master Data Management (MDM) with Stibo and designing large-scale data solutions Key Responsibilities: - Design and architect scalable data pipelines and solutions using AWS native services to support complex business requirements

Experience Range: 7 to 10 years of experience in advanced AWS data engineering, including significant expertise in Master Data Management (MDM) with Stibo and designing large-scale data solutions Key Responsibilities: - Design and architect scalable data pipelines and solutions using AWS native services to support complex business requirements - Develop, implement, and optimize ETL processes leveraging AWS technologies such as EMR, Redshift, Athena, and DMS

- Design and architect scalable data pipelines and solutions using AWS native services to support complex business requirements - Develop, implement, and optimize ETL processes leveraging AWS technologies such as EMR, Redshift, Athena, and DMS - Configure and manage real-time data streaming and ingestion frameworks utilizing Kinesis and Amazon API Gateway

- Collaborate with cross-functional teams to integrate data solutions with enterprise applications and analytics platforms - Ensure data security, quality, and compliance by implementing best practices and leveraging AWS security features - Lead technical reviews, mentor junior engineers, and drive adoption of emerging data technologies within the organization

Required Skills: - Advanced proficiency in AWS services including SNS, SQS, Amazon API Gateway, Athena, CloudFormation, CloudWatch, DMS, DynamoDB, EMR, Kinesis, Open Search, Redshift, SCT - Expertise in designing and managing data pipelines and ETL workflows on AWS

- Advanced proficiency in AWS services including SNS, SQS, Amazon API Gateway, Athena, CloudFormation, CloudWatch, DMS, DynamoDB, EMR, Kinesis, Open Search, Redshift, SCT - Expertise in designing and managing data pipelines and ETL workflows on AWS - Strong experience with Spark using Scala for large-scale data processing

- Hands-on experience with Oozie workflow scheduling and orchestration - Deep knowledge of real-time data streaming with AWS Kinesis - Proven ability to configure and optimize Amazon Redshift for analytics workloads

- Experience with DynamoDB for NoSQL database solutions - Ability to automate infrastructure and deployments using AWS CloudFormation - Proficient in monitoring and logging with AWS CloudWatch

- Ability to automate infrastructure and deployments using AWS CloudFormation - Proficient in monitoring and logging with AWS CloudWatch - Skill in managing data migration and schema transformation using AWS SCT and DMS

- Proficient in monitoring and logging with AWS CloudWatch - Skill in managing data migration and schema transformation using AWS SCT and DMS - Demonstrated expertise in implementing and integrating MDM solutions using Stibo

Preferred Skills: - Experience integrating AWS data solutions with third-party analytics and visualization tools - Proficiency in optimizing performance for large-scale distributed data systems

- Proficiency in optimizing performance for large-scale distributed data systems - Knowledge of emerging AWS data services and staying current with industry best practices - Experience with Open Search for search and analytics use cases

- Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline - AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional - Certification in Apache Spark or relevant big data technologies (preferred)

- Proven ability to configure and optimize Amazon Redshift for analytics workloads - Experience with DynamoDB for NoSQL database solutions - Ability to automate infrastructure and deployments using AWS CloudFormation

- Deep knowledge of real-time data streaming with AWS Kinesis - Proven ability to configure and optimize Amazon Redshift for analytics workloads - Experience with DynamoDB for NoSQL database solutions

- AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional - Certification in Apache Spark or relevant big data technologies (preferred) Employment type

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Status in our records: Live
First seen by us: Sep 1, 2026 · 47d ago
Recorded sightings: 98
Last seen by us: Oct 17, 2026

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Job description

View original posting ↗

Senior Tech Specialist, Applications & Platforms

Job requirements

Experience Range: 7 to 10 years of experience in advanced AWS data engineering, including significant expertise in Master Data Management (MDM) with Stibo and designing large-scale data solutions Key Responsibilities:

Design and architect scalable data pipelines and solutions using AWS native services to support complex business requirements
Develop, implement, and optimize ETL processes leveraging AWS technologies such as EMR, Redshift, Athena, and DMS
Configure and manage real-time data streaming and ingestion frameworks utilizing Kinesis and Amazon API Gateway
Monitor, troubleshoot, and enhance data infrastructure performance using CloudWatch and Open Search
Automate deployment and infrastructure provisioning with CloudFormation and manage schema migrations using SCT
Lead the implementation and integration of Master Data Management (MDM) solutions using Stibo within enterprise data platforms
Collaborate with cross-functional teams to integrate data solutions with enterprise applications and analytics platforms
Ensure data security, quality, and compliance by implementing best practices and leveraging AWS security features
Lead technical reviews, mentor junior engineers, and drive adoption of emerging data technologies within the organization

Required Skills:

Advanced proficiency in AWS services including SNS, SQS, Amazon API Gateway, Athena, CloudFormation, CloudWatch, DMS, DynamoDB, EMR, Kinesis, Open Search, Redshift, SCT
Expertise in designing and managing data pipelines and ETL workflows on AWS
Strong experience with Spark using Scala for large-scale data processing
Hands-on experience with Oozie workflow scheduling and orchestration
Deep knowledge of real-time data streaming with AWS Kinesis
Proven ability to configure and optimize Amazon Redshift for analytics workloads
Experience with DynamoDB for NoSQL database solutions
Ability to automate infrastructure and deployments using AWS CloudFormation
Proficient in monitoring and logging with AWS CloudWatch
Skill in managing data migration and schema transformation using AWS SCT and DMS
Demonstrated expertise in implementing and integrating MDM solutions using Stibo

Preferred Skills:

Experience integrating AWS data solutions with third-party analytics and visualization tools
Proficiency in optimizing performance for large-scale distributed data systems
Knowledge of emerging AWS data services and staying current with industry best practices
Experience with Open Search for search and analytics use cases
Background in mentoring and leading engineering teams in cloud data projects
Familiarity with advanced data governance and data quality frameworks in MDM environments

Desired Qualifications:

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a closely related discipline
AWS Certified Data Analytics – Specialty or AWS Certified Solutions Architect – Professional
Certification in Apache Spark or relevant big data technologies (preferred)

Employment type

Employee

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Location & working pattern

Hyderabad, Andhra Pradesh, India

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Principal Data Engineer-R01570250