Data Engineer

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field
• 2-4 years of experience (either in data or related fields) in AI/ML or data related roles
• Strong proficiency in Python and familiarity with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch) and familiarity with AI frameworks.
• Practical knowledge of data preprocessing, model optimization, and evaluation techniques.
• Experience with cloud platforms (AWS, Azure, or GCP) and containerize on tools (Docker, Kubernetes).
• Understanding of MLOps concepts and version control systems (Git).
• Working experience of SQL/NoSQL databases and data pipeline management tools
• Strong problem-solving mindset and willingness to learn
• Good communication and collaboration skills
• Business analysis

Projects

At OFI Services, we are committed to driving innovation through data, technology, and human insight. Our global teams collaborate to deliver transformative solutions that empower smarter decisions and operational excellence.

As we continue to expand our digital capabilities in India, we are looking for forward-thinking professionals who can shape the future of intelligent automation and AI within our organization.

We are looking for a Data Engineer to join our AI and analytics team. This role is for professionals who can design ETL pipelines, build data models, and deploy AI, ML solutions across business units. This position requires a strong technical foundation, problem-solving mindset, and the ability to collaborate across teams to turn business challenges into intelligent, data-driven solutions.

Key Responsibilities

• Build data pipelines and deploying AI/ML solutions to solve business challenges across different domains.
• Develop end-to-end AI/ML workflows including data ingestion, transformation, deployment, and monitoring
• Design and optimize ETL processes for seamless data integration across cloud and analytics platforms
• Integrate AI/ML models into production systems using APIs and microservices
• Monitor data quality, pipeline performance, and model reliability to ensure scalability and efficiency
• Contribute to data engineering standards, governance practices, and secure data management

What You’ll Gain

• Hands-on experience working on real-world projects
• Mentorship from senior consultants and technical leads
• Exposure to client-facing consulting environments
• Opportunities to build expertise in emerging AI technologies
• A structured learning and growth path within the organization

Preferred Skills

• Strong understanding of data engineering concepts including ETL/ELT, data pipelines, and data warehousing
• Proficiency in SQL and Python alongwith exposure to Generative AI, NLP, or LLM-based applications
• Experience with pipeline orchestration tools such as Apache Airflow, Azure Data Factory or similar platforms
• Familiarity with cloud platforms such as AWS, Azure, or GCP
• Exposure to big data technologies like Spark, Kafka, or Databricks
• Understanding of data quality, governance, and security best practices
• Familiarity with APIs, Git, Docker etc.