What you'll do:

• Analytics:
• Analyse business requirements and translate them into analytics solutions.
• Architect, design, and implement scalable data analytics solutions using Databricks, and other Azure cloud services.
• Lead data engineering initiatives, including data pipelines, data lakes, and data warehousing solutions.
• Develop and optimize data models for analytical and operational use cases.
• Implement and drive MLOps best practices, ensuring efficient deployment, monitoring, and management of machine learning models.
• Work closely with business stakeholders to understand data requirements and translate them into effective analytics solutions.
• Enable data visualization and business intelligence using tools such as Power BI.
• Ensure data security, compliance, and governance within Azure and associated technologies.
• Collaborate with cross-functional teams, including data scientists, engineers, and business analysts, to drive data-driven decision-making.
• Provide technical leadership and mentorship to the data engineering and analytics teams.
• Stay up to date with the latest advancements in data engineering, cloud analytics, and AI/ML technologies.
• Lead data modelling efforts, ensuring optimal database structures for analytics and reporting.
• Drive Power BI optimization strategies, including data model tuning, performance enhancements, and visualization best practices.
• Collaborate with Data Science teams to integrate AI/ML/GenAI solutions into the data ecosystem.
• Ensure data security, compliance, and governance across all data architectures.
• Provide technical leadership and mentorship to junior data engineers and architects.
• Ensure data quality, integrity, and reliability throughout the data lifecycle.
• Strong analytical and problem-solving skills.
• Experience with cloud platforms like Azure Synapse Analytics, Azure Data Factory, is a plus.
• Stakeholder Engagement:
• Work closely with cross-functional teams, including IT, Finance, and Operations, to understand business needs.
• Communicate complex data insights to non-technical stakeholders in an understandable manner.
• Act as the primary point of contact for all data analytics-related queries.
• Cost Optimization:
• Designing Cost-Efficient Data Architectures
• Cloud Cost Governance & Budgeting
• Optimizing Data Storage Costs
• Optimizing Compute & Processing Costs
• Automating Cost Monitoring & Reporting

• Continuous Improvement:
• Identify opportunities for process improvements and implement best practices in data analytics.
• Stay abreast of industry trends and advancements in data analytics.
• Promote a culture of continuous learning and development within the team.

Skill and knowledge you should possess:

• Bachelor’s degree in Business Administration, Information Technology, Data Science, or a related field. Master’s degree is a plus.
• 10-14 years of experience in Data Engineering, Analytics, Visualization, AI/ML.
• Hands-on expertise in Databricks and Microsoft Azure ecosystem.
• Strong knowledge of MLOps frameworks and best practices.
• Experience in building predictive and prescriptive models for various business use cases.
• Proficiency in Python, SQL, and Spark for data processing and analysis.
• Deep understanding of data pipelines, ETL processes, and cloud-based data lake solutions.
• Experience in developing and deploying AI/ML models
• Expertise in data governance, security, and compliance within cloud environments.
• Experience with Power BI, other visualization tools.
• Strong problem-solving and analytical skills.
• Excellent communication and stakeholder management skills.
• Domain experience in Manufacturing is preferred.
• Working experience in Gen-AI & Agentic AI
• Strong analytical and problem-solving skills with a keen attention to detail.
• Excellent communication and interpersonal skills.

Preferred Skills:

• Experience in the manufacturing industry.
• Familiarity with machine learning and advanced analytics techniques.
• Familiarity with Python for data analysis & automation is an advantage.