Data Engineer

Project Role : Data Engineer

Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems.

Must have skills : AWS Architecture

Good to have skills : Python (Programming Language)

Minimum 5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

Summary: As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to effectively migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide innovative solutions that enhance data accessibility and usability. AWS Data Architect to lead the design and implementation of scalable, cloud-native data platforms. The ideal candidate will have deep expertise in AWS data services, along with hands-on proficiency in Python and PySpark for building robust data pipelines and processing frameworks. Roles & Responsibilities: - Expected to be an SME. - Collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Provide solutions to problems for their immediate team and across multiple teams. - Mentor junior team members to enhance their skills and knowledge. - Continuously evaluate and improve data processes to ensure efficiency and effectiveness. - Design and implement enterprise-scale data lake and data warehouse solutions on AWS. - Lead the development of ELT/ETL pipelines using AWS Glue, EMR, Lambda, and Step Functions, with Python and PySpark. - Work closely with data engineers, analysts, and business stakeholders to define data architecture strategy. - Define and enforce data modeling, metadata, security, and governance best practices. - Create reusable architectural patterns and frameworks to streamline future development. - Provide architectural leadership for migrating legacy data systems to AWS. - Optimize performance, cost, and scalability of data processing workflows. Professional & Technical Skills: - Must To Have Skills: Proficiency in AWS Architecture. - Strong understanding of data modeling and database design principles. - Experience with ETL tools and data integration techniques. - Familiarity with data warehousing concepts and technologies. - Knowledge of programming languages such as Python or Java for data processing. - AWS Services: S3, Glue, Athena, Redshift, EMR, Lambda, IAM, Step Functions, CloudFormation or Terraform - Languages: Python ,PySpark .SQL - Big Data: Apache Spark, Hive, Delta Lake - Orchestration & DevOps: Airflow, Jenkins, Git, CI/CD pipelines - Security & Governance: AWS Lake Formation, Glue Catalog, encryption, RBAC - Visualization: Exposure to BI tools like QuickSight, Tableau, or Power BI is a plus Additional Information: - The candidate should have minimum 5 years of experience in AWS Architecture. - This position is based at our Pune office. - A 15 years full time education is required.