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Principal Data Engineer-R01570250

Hyderabad, Andhra Pradesh, India

Live, first seen by us 66 days ago
Pay
Pay not listed
Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting
Employment
Not stated

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
Apply at Brillio-2

Posting record

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Status in our records
Live
First seen by us
Sep 1, 202666 days ago
Recorded sightings
132
Last seen by us
Nov 6, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 66

Up longer than most. Similar jobs usually come down between day 6 and day 54.

Well past Brillio-2’s usual: its jobs come down by about day 25.

From 11,418 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.

Brillio-2 is hiring

46 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring has slowed
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Scala
  • AWS
  • DynamoDB
  • NoSQL
  • Redshift
  • Spark
Where the posting names them
- 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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Demand for Data Engineer roles

New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 839, the most 1,314, and the latest week had 1,082.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Engineer, by the work the posting describes.

Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.

Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.

An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.

US government figures for database architects

Median yearly pay, May 2025
$139,500
Expected change, 2025 to 2035
9.4% more jobsagainst 3.5% for all jobs

The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

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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Hyderabad, Andhra Pradesh, India

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