Senior Data Specialist
Primary Skills
Senior AWS Data Engineer
Experience: 7 – 12 Years
Location: Bangalore | Hyderabad | Pune | Chennai | Gurgaon
Company: Brillio
About Brillio
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.
Role Overview
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.
Required Technical Skills
AWS Services
Athena
SNS
SQS
CloudWatch
Macie
Kinesis
CloudFormation
EMR
OpenSearch
DynamoDB
Amazon API Gateway
AWS SCT (Schema Conversion Tool)
Redshift
AWS DMS
Data Engineering & Big Data
Apache Spark (Scala)
Oozie
ETL/ELT Development
Data Modeling
Batch & Real-Time Data Processing
Data Warehousing Concepts
Programming
Scala
SQL
Python (Good to Have)
Key Responsibilities
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.
Required Qualifications
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.
Preferred Qualifications
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.
Good to Have
Docker/Kubernetes
Machine Learning data pipelines
Data Quality Frameworks
Data Catalog & Metadata Management
Event-driven architecture and streaming platforms
Job requirements
Senior AWS Data Specialist
Experience: 7 – 12 Years
Location: Bangalore | Hyderabad | Pune | Chennai | Gurgaon
Company: Brillio
About Brillio
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.
Role Overview
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.
Required Technical Skills
AWS Services
Athena
SNS
SQS
CloudWatch
Macie
Kinesis
CloudFormation
EMR
OpenSearch
DynamoDB
Amazon API Gateway
AWS SCT (Schema Conversion Tool)
Redshift
AWS DMS
Data Engineering & Big Data
Apache Spark (Scala)
Oozie
ETL/ELT Development
Data Modeling
Batch & Real-Time Data Processing
Data Warehousing Concepts
Programming
Scala
SQL
Python (Good to Have)
Key Responsibilities
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.
Required Qualifications
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.
Preferred Qualifications
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.
Good to Have
Docker/Kubernetes
Machine Learning data pipelines
Data Quality Frameworks
Data Catalog & Metadata Management
Event-driven architecture and streaming platforms