Required Skills : Strong ETL ,SQL expert with knowledge on python. - ETL concepts
- Data Warehousing concepts
- Advanced SQL Concepts
- Data Validation/Data Quality Check
- CI/CD techniques.
- Programming language: JAVA, Python
- Cloud Platform: GCP
Primary Roles & Responsibilities : - Manage the end-to-end lifecycle of data pipelines, including extraction, transformation, and loading into the Google Warehouse (GCP).
- Conduct in-depth data analysis and apply statistical methods to derive insights.
- Execute code development within the designated DEV environment.
- Perform comprehensive validation and testing prior to deploying code to UAT or other staging environments.
- Document and maintain records of all test outcomes.
- Facilitate the code submission process by preparing ChangeLists for peer review.
- Oversee the final deployment of code across multiple environments, including UAT, PREPROD, and PROD.
Job Description: - Develop and manage ETL data pipelines to populate the data warehouse using various custom and third-party systems.
- Create, deploy, and refine comprehensive full-stack Data and BI solutions, covering everything from extraction and storage to transformation and visualization.
- Utilize SQL and Python to build and maintain robust data analysis scripts.
- Provide ongoing support and development for dashboards and reports via Google PLx and Looker Studio.
- Enhance existing business intelligence tools and create new dashboards to drive organizational growth.
- Conduct detailed data examinations and apply statistical analysis techniques.
- Monitor performance and implement necessary infrastructure optimizations
- Demonstrate excellent collaboration, interpersonal communication and written skills with ability to work in a team environment.
Minium Qualifaication:- Candidates must possess at least 6-8 years of professional experience.
- Due to the high-velocity nature of this project, individuals with extensive experience will achieve the most effective results.
Responsibilities in this role : - Design, develop, and maintain scalable and robust ETL/ELT processes and data pipelines using various tools and technologies.
- Build and optimize data warehouses, data lakes, and other data storage solutions to support analytical and operational needs.
- Implement data quality checks and monitoring to ensure the accuracy, completeness, and consistency of data.
- Work with large datasets, performing data modeling, schema design, and performance tuning.
- Create data models that are easy for BI tools to consume and build dashboard.