Hyderabad, Andhra Pradesh, India
Live, first seen by us 65 days agoWork setup in the employer’s posting: hybridFrom the employer’s 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
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
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
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
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Day 65
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Well past Brillio-2’s usual: its jobs come down by about day 25.
From 11,265 similar postings that came down, and 58 of Brillio-2’s. Coming down is not always a hire.
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- 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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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
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.
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.
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.
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Hyderabad, Andhra Pradesh, India
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