Senior Data Specialist - R01566949

Brillio is a leading digital technology consulting and solutions company focused on delivering transformative outcomes for enterprises through cloud, data, AI, and digital engineering solutions.

Brillio is a leading digital technology consulting and solutions company focused on delivering transformative outcomes for enterprises through cloud, data, AI, and digital engineering solutions.

We are looking for a highly skilled AWS Data Engineer with strong expertise in designing, developing, and maintaining large-scale cloud-native data platforms. The ideal candidate should have extensive experience with AWS data services, Spark-Scala, ETL development, real-time streaming, and data warehousing solutions.

We are looking for a highly skilled AWS Data Engineer with strong expertise in designing, developing, and maintaining large-scale cloud-native data platforms. The ideal candidate should have extensive experience with AWS data services, Spark-Scala, ETL development, real-time streaming, and data warehousing solutions.

• Athena
• SNS
• SQS
• CloudWatch
• Macie
• Kinesis
• CloudFormation
• EMR
• OpenSearch
• DynamoDB
• Amazon API Gateway
• AWS SCT (Schema Conversion Tool)
• Redshift
• AWS DMS
• Athena
• SNS
• SQS
• CloudWatch
• Macie
• Kinesis
• CloudFormation
• EMR
• OpenSearch
• DynamoDB
• Amazon API Gateway
• AWS SCT (Schema Conversion Tool)
• Redshift
• AWS DMS

• Apache Spark (Scala)
• Oozie
• ETL/ELT Development
• Data Modeling
• Batch & Real-Time Data Processing
• Data Warehousing Concepts
• Apache Spark (Scala)
• Oozie
• ETL/ELT Development
• Data Modeling
• Batch & Real-Time Data Processing
• Data Warehousing Concepts

• Scala
• SQL
• Python (Good to Have)
• Scala
• SQL
• Python (Good to Have)

• →Design, build, and maintain scalable data pipelines using AWS native services.
• →Develop high-performance data processing applications using Spark and Scala.
• →Build and optimize ETL/ELT frameworks for large-scale structured and unstructured datasets.
• →Implement real-time streaming solutions using Amazon Kinesis.
• →Design and manage data warehouses using Amazon Redshift.
• →Perform data migration and modernization projects using AWS DMS and SCT.
• →Create and manage workflow orchestration using Oozie.
• →Implement Infrastructure as Code (IaC) using AWS CloudFormation.
• →Configure monitoring, logging, and alerting using CloudWatch.
• →Manage data security, governance, and compliance using AWS Macie.
• →Develop API-based integrations using Amazon API Gateway.
• →Optimize performance, scalability, reliability, and cost of AWS workloads.
• →Collaborate with architects, business stakeholders, and cross-functional engineering teams to deliver cloud-native data solutions.
• →Design, build, and maintain scalable data pipelines using AWS native services.
• →Develop high-performance data processing applications using Spark and Scala.
• →Build and optimize ETL/ELT frameworks for large-scale structured and unstructured datasets.
• →Implement real-time streaming solutions using Amazon Kinesis.
• →Design and manage data warehouses using Amazon Redshift.
• →Perform data migration and modernization projects using AWS DMS and SCT.
• →Create and manage workflow orchestration using Oozie.
• →Implement Infrastructure as Code (IaC) using AWS CloudFormation.
• →Configure monitoring, logging, and alerting using CloudWatch.
• →Manage data security, governance, and compliance using AWS Macie.
• →Develop API-based integrations using Amazon API Gateway.
• →Optimize performance, scalability, reliability, and cost of AWS workloads.
• →Collaborate with architects, business stakeholders, and cross-functional engineering teams to deliver cloud-native data solutions.

• Bachelor's degree in Computer Science, Information Technology, Engineering, or related discipline.
• 7+ years of overall experience in Data Engineering and Cloud Data Platforms.
• Minimum 4+ years of hands-on AWS Data Engineering experience.
• Strong expertise in Spark-Scala development.
• Experience building enterprise-grade data lakes and data warehouses.
• Excellent SQL and performance tuning skills.
• Experience working in Agile/Scrum environments.
• AWS Certified Data Analytics – Specialty.
• AWS Certified Solutions Architect Associate/Professional.
• Experience with AWS Glue, Airflow, or Databricks.
• Exposure to CI/CD, DevOps, and Infrastructure Automation.
• Knowledge of data governance and security best practices.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or related discipline.
• 7+ years of overall experience in Data Engineering and Cloud Data Platforms.
• Minimum 4+ years of hands-on AWS Data Engineering experience.
• Strong expertise in Spark-Scala development.
• Experience building enterprise-grade data lakes and data warehouses.
• Excellent SQL and performance tuning skills.
• Experience working in Agile/Scrum environments.
• AWS Certified Data Analytics – Specialty.
• AWS Certified Solutions Architect Associate/Professional.
• Experience with AWS Glue, Airflow, or Databricks.
• Exposure to CI/CD, DevOps, and Infrastructure Automation.
• Knowledge of data governance and security best practices.

• Docker/Kubernetes
• Machine Learning data pipelines
• Data Quality Frameworks
• Data Catalog & Metadata Management
• Event-driven architecture and streaming platforms