Principal Consulting - Data&AI

Embed AI-first principles into delivery workflows, leveraging automation and intelligent orchestration where applicable. Lead end-to-end delivery of complex projects, ensuring solutions are scalable, robust, and aligned with client business outcomes. Drive engineering excellence through reusable components, accelerators, and scalable architecture. Oversee technical execution across multiple projects, ensuring adherence to best practices, quality standards, and compliance requirements. Collaborate with clients and internal stakeholders to define strategies, delivery plans, milestones, and risk mitigation approaches. Act as a technical point of contact for clients, translating business requirements into scalable technical solutions. Ensure delivery models are optimized for modern, AI-native execution, including integration of automation and intelligent processes. Monitor and evaluate emerging technologies to inform strategic direction. Lead innovation in delivery models, reusable assets, and accelerators to enhance efficiency and impact. Champion modern thinking and best practices across teams and engagements to foster a culture of continuous improvement. 20+ years of Data Engineering experience and Strong Experience in driving Enterprise Data Architecture, Azure Data services, Machine learning Offerings, Platform Modernizations. Strong Experience in large database solutions, on premises, cloud, and hybrid implementations Strong experience in Serverless Architecture/Microservices Strong experience of full application life cycle design tools and methodologies Strong experience in one or more technologies under each of the following Big Data Stack: Spark, Spark Streaming, Databricks, Kafka, Hadoop, Hive, HDInsight Database Stack: OLTP/OLAP, data storage mechanisms, columnar (RedShift, Vertica), OSS (MySQL, PostgreSQL, MariaDB), CosmosDB, MongoDB, Redis, Cassandra, key-value stores, graph databases, RDF triple stores Level 400 knowledge and engine-level debugging (e.g., CXPACKET analysis, disk throttling, IO/network contentions, performance optimizations) Data Engineering: Dimensional modelling, Lambda/Kappa architectures, time series data, Azure Stream Analytics, Azure Analysis Service Design and execution of large-scale data migrations using ADF, SSIS, Talend, Pentaho, Informatica Expertise in multi-tenant database design, platform security hardening, and implementation of data governance practices using open source or proprietary tools DataOps expertise Good experience in Agile Methodology & Expertise in Azure DevOps and Setting examples for good engineering practices and coding along the way through automation where possible. Industry experience in one or more of the following industries: automotive, energy, travel and transportation, financial services, government, health, manufacturing, media & communications, or retail/supply chain. Ensure adherence to coding standards, architectural integrity, and performance benchmarks. Support pre-sales and solutioning efforts with estimations, proof-of-concepts, and technical proposals. Build and maintain strong client relationships, ensuring high levels of satisfaction and value delivery. Ensure all deliverables meet quality standards, security, and regulatory requirements. Promote secure coding, test-driven development, and observability as default practices. Provide strategic guidance and execution oversight to ensure alignment with organizational goals.