Senior Technical Lead
India
Job Description
Senior Technical Lead
Bengaluru, Karnataka
Job Summary
Role Overview
We are seeking an experienced AWS Data Analyst / Data Engineer with strong expertise in SQL, AWS data services, data analysis, and requirement management. The ideal candidate will be responsible for analyzing complex datasets, managing data requirements, performing data validation and sign-off activities, and transforming business requirements into technical specifications and solutions.
Key Responsibilities
- Perform data analysis, data validation, reconciliation, and sign-off activities for enterprise data initiatives.
- Gather, analyze, and document business and technical requirements.
- Create detailed data mapping documents and technical specifications.
- Develop and optimize complex SQL and Advanced SQL queries for data analysis and reporting.
- Design, develop, and maintain AWS-based data pipelines and analytics solutions.
- Work with AWS Glue, Athena, Redshift, and MWAA (Managed Workflows for Apache Airflow) to process and manage large-scale datasets.
- Collaborate with business stakeholders, product owners, and technical teams to translate business requirements into technical solutions.
- Support data migration, transformation, and integration initiatives.
- Implement and maintain DevOps practices within the data engineering lifecycle.
- Ensure data quality, governance, and compliance through robust validation frameworks.
- Participate in solution design reviews, deployment activities, and production support.
Mandatory Skills
| Skill | Proficiency |
|---|---|
| SQL & Advanced SQL for Data Analysis, Validation, and Sign-off | Expert (5/5) |
| AWS Glue | Expert (5/5) |
| AWS Athena | Expert (5/5) |
| AWS Redshift | Expert (5/5) |
| AWS MWAA (Apache Airflow) | Expert (5/5) |
| Data Analysis & Requirement Management | Expert (5/5) |
| Data Mapping | Expert (5/5) |
| AWS Cloud Services | Advanced (4/5) |
| Ability to Convert Business Requirements into Technical Documentation | Advanced (4/5) |
| DevOps | Intermediate (3/5) |
Good-to-Have Skills
- ETL Development
- Data Warehousing Concepts
- Python Programming
- Data Modeling
- CI/CD implementation in cloud environments
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
- Experience working in Banking, Financial Services, or Enterprise Data Platforms is preferred.
- Strong analytical, problem-solving, and stakeholder management skills.
- Experience working in Agile/Scrum delivery environments.
Key Competencies
- Data Analysis & Validation
- Requirement Gathering & Documentation
- Data Mapping & Lineage
- AWS Data Services
- Stakeholder Communication
- Technical Solution Design
- Data Quality Management
- DevOps & Automation
Key Responsibilities
Role Overview
We are seeking an experienced AWS Data Analyst / Data Engineer with strong expertise in SQL, AWS data services, data analysis, and requirement management. The ideal candidate will be responsible for analyzing complex datasets, managing data requirements, performing data validation and sign-off activities, and transforming business requirements into technical specifications and solutions.
Key Responsibilities
- Perform data analysis, data validation, reconciliation, and sign-off activities for enterprise data initiatives.
- Gather, analyze, and document business and technical requirements.
- Create detailed data mapping documents and technical specifications.
- Develop and optimize complex SQL and Advanced SQL queries for data analysis and reporting.
- Design, develop, and maintain AWS-based data pipelines and analytics solutions.
- Work with AWS Glue, Athena, Redshift, and MWAA (Managed Workflows for Apache Airflow) to process and manage large-scale datasets.
- Collaborate with business stakeholders, product owners, and technical teams to translate business requirements into technical solutions.
- Support data migration, transformation, and integration initiatives.
- Implement and maintain DevOps practices within the data engineering lifecycle.
- Ensure data quality, governance, and compliance through robust validation frameworks.
- Participate in solution design reviews, deployment activities, and production support.
Mandatory Skills
| Skill | Proficiency |
|---|---|
| SQL & Advanced SQL for Data Analysis, Validation, and Sign-off | Expert (5/5) |
| AWS Glue | Expert (5/5) |
| AWS Athena | Expert (5/5) |
| AWS Redshift | Expert (5/5) |
| AWS MWAA (Apache Airflow) | Expert (5/5) |
| Data Analysis & Requirement Management | Expert (5/5) |
| Data Mapping | Expert (5/5) |
| AWS Cloud Services | Advanced (4/5) |
| Ability to Convert Business Requirements into Technical Documentation | Advanced (4/5) |
| DevOps | Intermediate (3/5) |
Good-to-Have Skills
- ETL Development
- Data Warehousing Concepts
- Python Programming
- Data Modeling
- CI/CD implementation in cloud environments
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
- Experience working in Banking, Financial Services, or Enterprise Data Platforms is preferred.
- Strong analytical, problem-solving, and stakeholder management skills.
- Experience working in Agile/Scrum delivery environments.
Key Competencies
- Data Analysis & Validation
- Requirement Gathering & Documentation
- Data Mapping & Lineage
- AWS Data Services
- Stakeholder Communication
- Technical Solution Design
- Data Quality Management
- DevOps & Automation
Skill Requirements
Role Overview
We are seeking an experienced AWS Data Analyst / Data Engineer with strong expertise in SQL, AWS data services, data analysis, and requirement management. The ideal candidate will be responsible for analyzing complex datasets, managing data requirements, performing data validation and sign-off activities, and transforming business requirements into technical specifications and solutions.
Key Responsibilities
- Perform data analysis, data validation, reconciliation, and sign-off activities for enterprise data initiatives.
- Gather, analyze, and document business and technical requirements.
- Create detailed data mapping documents and technical specifications.
- Develop and optimize complex SQL and Advanced SQL queries for data analysis and reporting.
- Design, develop, and maintain AWS-based data pipelines and analytics solutions.
- Work with AWS Glue, Athena, Redshift, and MWAA (Managed Workflows for Apache Airflow) to process and manage large-scale datasets.
- Collaborate with business stakeholders, product owners, and technical teams to translate business requirements into technical solutions.
- Support data migration, transformation, and integration initiatives.
- Implement and maintain DevOps practices within the data engineering lifecycle.
- Ensure data quality, governance, and compliance through robust validation frameworks.
- Participate in solution design reviews, deployment activities, and production support.
Mandatory Skills
| Skill | Proficiency |
|---|---|
| SQL & Advanced SQL for Data Analysis, Validation, and Sign-off | Expert (5/5) |
| AWS Glue | Expert (5/5) |
| AWS Athena | Expert (5/5) |
| AWS Redshift | Expert (5/5) |
| AWS MWAA (Apache Airflow) | Expert (5/5) |
| Data Analysis & Requirement Management | Expert (5/5) |
| Data Mapping | Expert (5/5) |
| AWS Cloud Services | Advanced (4/5) |
| Ability to Convert Business Requirements into Technical Documentation | Advanced (4/5) |
| DevOps | Intermediate (3/5) |
Good-to-Have Skills
- ETL Development
- Data Warehousing Concepts
- Python Programming
- Data Modeling
- CI/CD implementation in cloud environments
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
- Experience working in Banking, Financial Services, or Enterprise Data Platforms is preferred.
- Strong analytical, problem-solving, and stakeholder management skills.
- Experience working in Agile/Scrum delivery environments.
Key Competencies
- Data Analysis & Validation
- Requirement Gathering & Documentation
- Data Mapping & Lineage
- AWS Data Services
- Stakeholder Communication
- Technical Solution Design
- Data Quality Management
- DevOps & Automation
Other Requirements
Role Overview
We are seeking an experienced AWS Data Analyst / Data Engineer with strong expertise in SQL, AWS data services, data analysis, and requirement management. The ideal candidate will be responsible for analyzing complex datasets, managing data requirements, performing data validation and sign-off activities, and transforming business requirements into technical specifications and solutions.
Key Responsibilities
- Perform data analysis, data validation, reconciliation, and sign-off activities for enterprise data initiatives.
- Gather, analyze, and document business and technical requirements.
- Create detailed data mapping documents and technical specifications.
- Develop and optimize complex SQL and Advanced SQL queries for data analysis and reporting.
- Design, develop, and maintain AWS-based data pipelines and analytics solutions.
- Work with AWS Glue, Athena, Redshift, and MWAA (Managed Workflows for Apache Airflow) to process and manage large-scale datasets.
- Collaborate with business stakeholders, product owners, and technical teams to translate business requirements into technical solutions.
- Support data migration, transformation, and integration initiatives.
- Implement and maintain DevOps practices within the data engineering lifecycle.
- Ensure data quality, governance, and compliance through robust validation frameworks.
- Participate in solution design reviews, deployment activities, and production support.
Mandatory Skills
| Skill | Proficiency |
|---|---|
| SQL & Advanced SQL for Data Analysis, Validation, and Sign-off | Expert (5/5) |
| AWS Glue | Expert (5/5) |
| AWS Athena | Expert (5/5) |
| AWS Redshift | Expert (5/5) |
| AWS MWAA (Apache Airflow) | Expert (5/5) |
| Data Analysis & Requirement Management | Expert (5/5) |
| Data Mapping | Expert (5/5) |
| AWS Cloud Services | Advanced (4/5) |
| Ability to Convert Business Requirements into Technical Documentation | Advanced (4/5) |
| DevOps | Intermediate (3/5) |
Good-to-Have Skills
- ETL Development
- Data Warehousing Concepts
- Python Programming
- Data Modeling
- CI/CD implementation in cloud environments
Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
- Experience working in Banking, Financial Services, or Enterprise Data Platforms is preferred.
- Strong analytical, problem-solving, and stakeholder management skills.
- Experience working in Agile/Scrum delivery environments.
Key Competencies
- Data Analysis & Validation
- Requirement Gathering & Documentation
- Data Mapping & Lineage
- AWS Data Services
- Stakeholder Communication
- Technical Solution Design
- Data Quality Management
- DevOps & Automation
Information at a Glance