• Design and optimize scalable data pipelines and data architecture. • Build cloud-native data solutions using Azure, Databricks ( Unity Catalog & Delta Lake), and other big data technologies. • Build and maintain DBT models and understand the data domains like finance, e-commerce, pharma, and supply chain. • Collaborate with business stakeholders and analysts to deliver data-driven solutions. • Apply CI/CD practices and continuously improve performance, scalability, and security. • Contribute to a strong data culture through continuous learning and knowledge sharing.

• Manages the overall data platform and infrastructure and mentors the team of data engineers • Supports developing processes, and expanding technology roadmap, planning features, measuring outputs, and ensuring quality products • Derives analytical insights from a variety of business contexts and communicates those insights effectively to stakeholders • Manages design and development of software and processes to support large scale, efficient data pipelines • Optimizes the availability of data to generate insights and address business needs • Translates technical business goals and requirements into designs utilizing best practice design patterns • Partners with engineering leads, product managers, and design leads in shaping and guiding the technical direction for the data engineering team • Plans, prioritizes and executes data production projects and processes • Develops the standards and processes required to ensure high-quality data products • Participates in code reviews and helps lead technical discussions • Manages the automation of key ETL / ELT processes for large volumes of data

• Analyze and derive value from data through the application methods such as mathematics, statistics, computer science, machine learning and data visualization • Understand business challenges, create valuable actionable insights about the data, and communicate your findings to the business • Enable data-driven decision making by creating custom models or prototypes from trends or patterns discerned and by underscoring implications • Coordinate with other technical/functional teams to implement models and monitor results • Develop data hypotheses and methods, train and evaluate analytics models, share insights and findings and continues to iterate with additional data • Develop processes, techniques, and tools to analyze and monitor model performance while ensuring data accuracy

• Lead the design and implementation of end-to-end data architectures supporting complex client implementations. • Develop and maintain conceptual, logical, and physical data models across multiple systems and platforms. • Architect and document source-to-target mappings, transformation logic, and data lineage across heterogeneous data models. • Ensure data solutions align with scalability, performance, security, and governance best practices. • Serve as the primary data architecture lead during client onboarding and implementation engagements. • Facilitate client workshops, discovery sessions, and data mapping reviews. • Present architecture designs, data flows, and implementation strategies to technical and non-technical client audiences. • Act as a trusted technical advisor, clearly articulating design options, trade-offs, and recommendations. • Design and implement cloud-native data solutions on Amazon Web Services (AWS). • Leverage AWS services such as S3, EMR, Glue, Athena, Redshift, EC2, Lambda, and related components to build scalable data pipelines.