AWS Glue/Pyspark/Redshift/SQL- Senior Technical Specialist

Job Title: Senior Technical Specialist

Location: Bengaluru, Mumbai, Hyderabad.

 We are looking for an experienced Senior Data Engineer / AWS Data Engineer with 8 years of hands-on experience in designing, developing, and maintaining scalable data engineering solutions. The ideal candidate should have strong expertise in AWS data services, Python, PySpark, SQL, ETL, infrastructure as code, and data orchestration.The candidate will be responsible for building robust data pipelines, integrating cloud and on-premises data sources, optimizing data processing workflows, and supporting enterprise-scale data platforms.

TechnologyRequired Expertise

AWS  Lambda, Glue, SNS, orchestration and related data services

Python Strong hands-on experience

PySpark Strong hands-on experience

SQL  Advanced SQL, query optimization, data transformation

Redshift Development, optimization, data loading

RDS  Database development and management

SSIS  ETL development and maintenance

SSMS  SQL Server development and troubleshooting

Terraform  Infrastructure as Code

YAML  Configuration/automation

Git  Version control and source code management

Podman Containerization

VS Code Development environment

Good to Have

• Experience with Connect
• Experience with TOLSE / TOLENT
• Experience with CI/CD and DevOps practices.
• Experience working in Agile/Scrum environments.
• Knowledge of cloud security, IAM, monitoring, and logging.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
• 8 years of professional experience in data engineering, ETL, cloud data platforms, or related technologies.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration skills.
• Ability to work independently as well as within a cross-functional team.

Target Profile: Senior Data Engineer / AWS Data Engineer / Lead Data Engineer with 8years of experience

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Develop cloud-native data solutions using AWS services, including Lambda, Glue, SNS, and orchestration services.
• Build and optimize data processing jobs using Python and PySpark.
• Develop complex SQL queries, stored procedures, and data transformations.
• Work with Amazon Redshift and Amazon RDS for data storage, processing, and analytics.
• Develop and maintain ETL packages and workflows using SSIS.
• Use SSMS for database development, troubleshooting, and performance optimization.
• Implement infrastructure and configuration using Terraform and YAML.
• Work with Git for source code management, branching, merging, and version control.
• Containerize and manage development workloads using Podman.
• Use VS Code as the primary development environment.
• Implement event-driven and automated workflows using AWS services such as Lambda, SNS, and orchestration frameworks.
• Monitor, troubleshoot, and optimize data pipelines and AWS workloads.
• Ensure data quality, reliability, security, and performance across data platforms.
• Collaborate with architects, developers, business analysts, and other stakeholders to deliver data solutions.
• Participate in code reviews, technical discussions, and production support activities.