Principal Data Engineer-R01570250
Hyderabad, Andhra Pradesh, India
- Pay
- Salary not listed in the saved posting
- Work setup
Hybrid — work setup source
Work setup in the employer’s listing: hybrid
From the employer’s posting- Employment
- Unconfirmed
What you’ll work on
Full postingDesign 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 qualificationsCore 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 — Tool mentions in context
- 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
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 1, 2026 · 47d ago
- Recorded sightings
- 98
- Last seen by us
- Oct 17, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Job description
Job requirements
- 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
- 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
- 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
- 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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Source details
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- Pay
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- Location & working pattern
Hyderabad, Andhra Pradesh, India
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