Data Engineer

Responsibilities About the role We are looking for a dynamic Data Engineer who is dedicated, takes ownership of their work, and is committed to developing high-quality, scalable data solutions. If you are ready for continuous learning and improvement with hands-on involvement in data engineering tasks, in a dynamic environment, we’d love to hear from you! What You'll Do Build and sustain reliable data pipelines and architectures using AWS services like S3, Lambda, SNS, EC2, IAM, and KMS, along with Snowflake capabilities such as snowpipe, streams, tasks, and stored procedures. Ensure the flawless completion of data engineering tasks by writing readable, maintainable code that follows coding guidelines and data protection standards. Implement and manage BI/DW, ETL, big data, cloud, data security, SQL, and data visualization concepts to build world-class data solutions. Develop code with established controls, policies, and recommended strategies to ensure compliance and high-quality deliverables. Engage in requirement analysis, testing, debugging, documentation, and quality review to understand and build basic data management processes, models, and architectures. Leverage AI-powered engineering tools, including GitHub Copilot and other approved GenAI solutions, to improve efficiency, code quality, documentation, test case generation, and troubleshooting while ensuring compliance with organizational security, privacy, and responsible AI guidelines. Demonstrate an outlook of AI adoption and continuous learning. Proactively find opportunities to use AI-assisted development techniques to speed up delivery, automate repetitive tasks, improve data engineering workflows, and increase operational efficiency. Communicate assumptions, seek clarification on tasks to minimize the need for rework, and actively participate in team meetings and discussions. Follow established project execution processes, coding standards, and industry guidelines to ensure high-quality outcomes. Get actively involved in training, self-development, and knowledge sharing, contributing to organization-level cloud initiatives. Solve problems with analytical thinking, applying root cause analysis to determine effective solutions. Adapt seamlessly between working independently and collaborating with a team to achieve ambitious goals. Qualifications Who You Are Education: Graduate - Bachelor's degree (any stream) Ability: 2-4 years of experience in data engineering with a proven track record. Proficiency in Python, SQL, and working with relational databases. Experience in building and optimizing data pipelines. Experience working with CI/CD pipelines in GitHub and Jenkins. Excellent communication and collaboration skills. Must-have Skills: Broad background in AWS offerings including S3, Lambda, SNS, EC2, IAM, and KMS. Skilled in CI/CD pipelines within GitHub and Snowflake functionalities such as streams, tasks, stored procedures, snowpipe, and data sharing. Good to have Skills: Hands-on experience or familiarity with one or more of the following technologies: Database, Data Visualization (Power BI), Scripting, ETL (Informatica PowerCenter). Nice to have AWS Cloud certification.