Senior Data & ML Engineer

Role : Senior Data & ML EngineerExperience : 8+ Years

Work Timings : 2 : 00 PM - 11 : 00 PM IST

Notice Period : Immediate - 15 Days

Cloud Platform : AWS required

Employment Type : Full-time

Role Overview :

We are looking for an experienced Senior Data & ML Engineer with strong expertise in data engineering, SQL, cloud platforms, machine learning and analytics. The ideal candidate should have hands-on experience working with large and complex datasets and building scalable data solutions that support advanced analytics, machine learning and emerging Generative AI use cases.

The role requires strong programming and data engineering capabilities along with an understanding of cloud security, governance, BI platforms and modern ML technologies.

Key Responsibilities :

• Design, develop and optimise scalable data solutions across heterogeneous data sources.

• Develop complex SQL queries and perform query optimisation and performance tuning.

• Build data validation, quality and automation processes.

• Work with large, complex and multi-dimensional structured and unstructured datasets.

• Develop data solutions using Python, SQL and Scala; Java knowledge is an added advantage.

• Work with data processing and ML technologies including Spark and Databricks.

• Support machine learning use cases using frameworks such as TensorFlow, scikit-learn and PyTorch.

• Leverage AWS services for data storage, compute, orchestration and monitoring.

• Develop data pipelines and solutions that support advanced analytics and ML workloads.

• Work with BI and analytics platforms such as Sigma Computing, Tableau, Power BI and MicroStrategy.

• Enable self-service and operational reporting through reliable and governed data solutions.

• Implement data governance, quality, lineage and compliance practices across cloud environments.

• Apply security controls including RBAC, encryption and secure-by-design principles.

• Analyse complex datasets to identify insights and enable advanced analytics and ML use cases.

• Collaborate with Data Scientists, ML Engineers, BI teams and business stakeholders to deliver data-driven solutions.

• Support the integration of Generative AI and modern ML capabilities into data engineering workflows.