Data Science & Engineering Lead

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Science & Engineering Lead based in India.

This role sits at the intersection of advanced data engineering and applied machine learning, driving end-to-end AI and data innovation across complex, large-scale systems. You will lead the design, development, and deployment of machine learning models and data platforms that generate actionable business insights and production-ready intelligence. The position combines hands-on technical execution with architectural ownership, spanning ML model development, data pipelines, and cloud-native infrastructure. You will work with modern AI frameworks, distributed systems, and big data technologies to build scalable, high-performance solutions. The role also involves mentoring engineers and shaping best practices across data science, MLOps, and data engineering functions. This is a high-impact leadership opportunity in a fast-evolving, innovation-driven environment focused on real-world AI applications.

Accountabilities

• Lead the design and implementation of supervised and unsupervised machine learning models, including regression, classification, ensemble methods, and advanced neural network architectures.
• Drive development of deep learning systems such as CNNs, RNNs, GANs, Transformers, and other state-of-the-art AI models for real-world applications.
• Oversee NLP and computer vision initiatives using modern frameworks and libraries to solve complex data problems.
• Architect and maintain scalable data pipelines for batch and streaming data using ETL tools and orchestration frameworks.
• Design and optimize lakehouse and data warehouse architectures, including Delta/Iceberg and bronze-silver-gold data models.
• Lead development of robust ETL workflows using tools such as Airflow, DBT, and Airbyte.
• Build and optimize cloud-native data and AI infrastructure on AWS or Azure, including services for compute, storage, and streaming.
• Oversee MLOps pipelines to ensure scalable, reliable, and automated deployment of machine learning models.
• Develop and maintain OLTP and OLAP data models across relational and NoSQL databases.
• Guide data visualization and BI initiatives using tools such as Power BI, Tableau, or QuickSight.
• Mentor and support junior engineers, fostering best practices in AI, ML, and data engineering.
  
  

Requirements

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; Master's or PhD preferred.
• 7+ years of experience in data science, machine learning, or data engineering roles.
• Strong hands-on expertise in supervised and unsupervised learning, deep learning, and neural network architectures.
• Advanced proficiency in Python and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
• Experience working with LLM tools and frameworks such as LangChain, Hugging Face, or OpenAI APIs.
• Strong background in big data processing using Spark and related distributed computing frameworks.
• Proven experience designing and deploying scalable data pipelines and ETL workflows.
• Deep understanding of cloud platforms (AWS or Azure), including services such as Lambda, Kinesis, Kafka, IAM, and networking.
• Hands-on experience with MLOps platforms such as SageMaker, Databricks, or Azure ML Studio.
• Strong knowledge of lakehouse architectures, data governance, and data quality frameworks.
• Experience with relational and NoSQL databases for both OLTP and OLAP systems.
• Strong leadership and mentoring abilities with excellent communication and cross-functional collaboration skills.
• Experience with Infrastructure as Code tools such as Terraform or CloudFormation is highly desirable.
  
  

Benefits

• Opportunity to lead end-to-end AI and data initiatives in a high-growth, innovation-driven environment.
• Remote-friendly work model based in India.
• Exposure to cutting-edge machine learning, GenAI, and large-scale data engineering systems.
• Strong leadership responsibility with ownership of architecture and technical direction.
• Collaborative and engineering-focused culture emphasizing innovation and continuous learning.
• Access to modern cloud platforms and advanced AI/ML tooling ecosystems.
• Competitive compensation aligned with experience and leadership level.
  
  

How Jobgether Works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.