About the role
Job Title: Senior Technical Specialist
Education: Any Graduate
Experience: 10+years
Location: Bengaluru, Mumbai, Hyderabad.
We are looking for an experienced Senior Data Engineer / AWS Data Engineer with 10–12 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
AWSLambda, Glue, SNS, orchestration and related data services
PythonStrong hands-on experience
PySparkStrong hands-on experience
SQLAdvanced SQL, query optimization, data transformation
RedshiftDevelopment, optimization, data loading
RDSDatabase development and management
SSISETL development and maintenance
SSMSSQL Server development and troubleshooting
TerraformInfrastructure as Code
YAMLConfiguration/automation
GitVersion control and source code management
PodmanContainerization
VS CodeDevelopment 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.
10 -12 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 10 -12 years 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.