njoyn
AWS Data Engineer / PySpark Developer
CGI
Bengaluru, IND
Full-time
Senior · 4+ years experience
Onsite
Discovered 3 weeks ago
AWSPythonPySparkSQLMongoDBMongoDB Atlas
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AWSPythonPySpark
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AWSPythonPySparkSQLMongoDBMongoDB Atlas
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Position Description:
Founded in 1976, CGI is among the largest independent IT and business consulting services firms in the world. With 94,000 consultants and professionals across the globe, CGI delivers an end-to-end portfolio of capabilities, from strategic IT and business consulting to systems integration, managed IT and business process services and intellectual property solutions. CGI works with clients through a local relationship model complemented by a global delivery network that helps clients digitally transform their organizations and accelerate results. CGI Fiscal 2024 reported revenue is CA$14.68 billion and CGI shares are listed on the TSX (GIB.A) and the NYSE (GIB). Learn more at cgi.com. Job Title: AWS Data Engineer / PySpark Developer Position: Senior Software Engineer Experience: 5- 8 Years Category: Software Development/ Engineering Shift: General Main location: Hyderabad, Bangalore, Chennai Position ID: J0726-2568 Employment Type: Full Time Education Qualification: Bachelor's degree in Computer Science or related field or higher with minimum 4 years of relevant experience. We are looking for an experienced AWS Data Engineer / PySpark Developer with around 5 years of hands-on experience in AWS, Python, PySpark, SQL, and NoSQL databases. The candidate should have strong experience in developing scalable data solutions, cloud-based ETL pipelines, production support, debugging, CI/CD, and containerized environments. The ideal candidate will possess strong problem-solving and analytical skills, along with the ability to collaborate effectively with technical teams, business stakeholders, and cross-functional teams in an Agile environment.
Your future duties and responsibilities:
- Design, develop, and maintain scalable data engineering and ETL solutions using Python and PySpark. Develop and optimize PySpark applications for large-scale data processing. Troubleshoot performance issues, data quality problems, job failures, and other challenges in PySpark-based applications. Develop data pipelines using AWS Glue and implement workflow orchestration using AWS Step Functions and/or Apache Airflow. Work with AWS services including IAM, Lambda, Glue, Redshift, and CloudWatch. Develop and optimize complex SQL queries for data extraction, transformation, and analysis. Work with NoSQL databases such as MongoDB and MongoDB Atlas. Implement data solutions that meet scalability, reliability, security, and performance requirements. Monitor production data pipelines and troubleshoot failures using AWS CloudWatch and application logs. Perform root-cause analysis for production incidents and document issues, resolutions, and preventive actions. Develop and maintain unit and automation tests using frameworks/tools such as JUnit, Cucumber, and Selenium, as applicable. Implement and maintain CI/CD pipelines using Jenkins and follow established deployment processes. Work with Docker and Kubernetes, including AWS container orchestration platforms such as EKS/ECS. Participate in deployment activities across development, testing, and production environments. Follow DevOps best practices for source control, automated builds, testing, deployment, monitoring, and release management. Develop dashboards and reports using Power BI, preferably, to provide meaningful insights into business and operational data. Participate in Agile/Scrum ceremonies, sprint planning, daily stand-ups, retrospectives, and backlog discussions. Collaborate with developers, architects, QA teams, DevOps engineers, business analysts, and other stakeholders. Communicate technical issues, solutions, project status, and risks effectively to technical and non-technical stakeholders.
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