ðŸ“ Job Summary

DXC Technology is looking for an experienced Data Engineer to design, build, and optimize reliable data pipelines and systems to support large-scale data science and machine learning initiatives. You will collaborate closely with data scientists, product managers, and other stakeholders to deliver robust, scalable, and production-ready data infrastructure using modern tools such as Pandas, SQL, Kedro, and AWS. This role is ideal for someone passionate about data architecture, automation, and enabling ML-powered solutions across the enterprise.

🎯 Key Responsibilities

• 🔧 Design and develop scalable and maintainable ETL/ELT pipelines using tools like Pandas, SQL, and Kedro.
• ☁️ Work with cloud infrastructure (especially AWS) to orchestrate workflows and deploy data services (S3, EC2, Lambda, Glue, SageMaker).
• 🔗 Integrate data from multiple sources, ensuring data quality, consistency, and security.
• 📦 Support deployment of machine learning models by managing structured data pipelines and feature stores.
• 📊 Build and maintain data validation and monitoring tools to ensure reliability of pipelines.
• 📁 Develop infrastructure and frameworks to support reproducible analysis, model training, and experimentation.
• 🤝 Collaborate with data scientists, ML engineers, and product teams to meet data and business requirements.
• 📜 Maintain thorough documentation and follow software engineering best practices including version control, testing, and code reviews.

🛠️ Required Skills & Experience

• 5+ years of experience as a Data Engineer or in a related data infrastructure role.
• Strong proficiency in Python with experience using Pandas and SQL for data processing.
• Hands-on experience with Kedro for pipeline creation and workflow reproducibility.
• In-depth knowledge of AWS services such as S3, EC2, Lambda, Glue, and SageMaker.
• Solid understanding of data modeling, data warehousing, and data lake architectures.
• Familiarity with version control systems like Git and collaborative development workflows.
• Excellent communication skills with the ability to explain technical solutions to non-technical teams.
• Strong problem-solving mindset and attention to performance, reliability, and security.

🌟 Nice to Have

• Experience with MLOps or ML infrastructure design (e.g., CI/CD for models, model registry, feature stores).
• Exposure to other cloud platforms (e.g., Google Cloud, Microsoft Azure).
• Familiarity with data visualization tools and libraries (e.g., Seaborn, Plotly, Tableau).
• Understanding of Langchain, LLMs, or other NLP frameworks as part of ML pipeline integration.
• Knowledge of containerization tools like Docker and orchestration systems such as Airflow, Kubernetes

Education Level : Bachelor's Degree

Technical Education : N/A

Certificate : N/A

Industrial Certificate : Experience

Key Skills
Programming & Development, Data Tools & Libraries, Attention to Detail, Problem-Solving & Troubleshooting, Visualization & Reporting

Other Skills
Time Management