AI/ML Data Solution Architecture Ability to define data architecture strategy that align with business goals for AI use cases and ensures data availability & data accuracy. Ensuring data quality by implementing and enforcing data governance policies and best practices Technology evaluation & selection Execute Proof of concept and Proof of value for various technology solutions and frameworks Continuous Learning - Staying up to date with emerging technologies and trends in Data Engineering, AI / ML, and GenAI, and making recommendations for their adoption wherever appropriate Team Management Responsible for leading a team of data architects and data engineers, as well as coordinating with vendors and technology partners Collaboration & communication Collaborate and work closely with executives, stakeholder and business teams to effectively communicate architecture strategy & clearly articulate the business value.
Suitable candidate be able to demonstrate strong experience in the following areas
- Data Engineering Hands-on experience with data engineering tools such as Talend (or Informatica or AbInitio), Databricks (or Spark), and HVR (or Attunity or Golden Gate or Equalum). Working knowledge of data build tools, Azure Data Factory, continuous integration and continuous delivery (CI/CD), automated testing, data lakes, data warehouses, big data, Collibra, and Unity Catalog Basic knowledge of building analytics applications using Azure Purview, Power BI, Spotfire, and Azure Machine Learning.
AI & ML -
Conceptualize & design end-to-end solution view of sourcing data, pre-processing data, feature stores, model development, evaluation, deployment & governance
Define model development best practices, create POVs on emerging AI trends, drive the proposal responses, help solving complex analytics problems and strategize the end-toend implementation frameworks & methodologies
Thorough understanding of database, streaming & analytics services offered by popular cloud platforms (Azure, AWS, GCP) and hands-on implementation of building machine learning pipeline with at least one of the popular cloud platforms
Expertise on Large Language Model preferred with exposure to implementing generative AI using ChatGPT / Open AI and other models. Harvesting Models from open source will be an added advantage
Good understanding of statistical analysis, data analysis and knowledge of data management & visualization techniques
Exposure to other AI Platforms & products (Kore.ai, expert.ai, Dataiku etc.) desired Hands-on development experience in Python/R is a must and additional hands-on experience on few other procedural/object-oriented programming languages (Java, C#, C++) is desirable.
Leadership skills to drive the AI/ML related conversation amidst CXO, Senior Leadership and making impactful presentations to customer organizations
Stakeholder Management & Communication Skills
Excellent communication, negotiation, influencing and stakeholder management skills
Preferred to have experience in project management, particularly in executing projects using Agile delivery frameworks Customer focus and excellent problem-solving skills
Qualification
BE or MTech (BSc or MSc) in engineering, sciences, or equivalent relevant experience required.
Total 15+ years of experience and 10+ years of experience in building/managing/administrating data and analytics applications is required
Designing solution architecture and present the architecture in architecture review forums
Additional Qualifications
Ability to define best practices for data governance, data quality, and data lineage, and to operationalize those practices.
Proven track record of designing and delivering solutions that comply with industry regulations and legislation such as GxP, SoX, HIPAA, and GDPR
