Tech Analyst, Data & AI

• Design & Implementation: Manage implementation of solutions for exploratory data analysis and conducts implementation assessments based on Architecture Overview Documents (AOD) and Detailed Data Solutions
• Provide accurate effort estimations and assess feasibility of proposed architectures and data models
• Design, undertake and analyze data to determine patterns and insights that can optimize data ingestion and data presentation
• Pipeline Design & Development: Design and develop cost-effective, scalable ELT pipelines using reusable components and frameworks
• Support the delivery of AI and data projects by designing and implementing streaming and/or batch pipelines
• Design and document pipeline implementation strategies including, scheduling of jobs and workflows, dependencies, error handling, monitoring and alerting and unit testing
• Monitor and resolve alerts/failures in prod/non-prod environments to ensure operational reliability
• Participate in peer reviews and oversee the review and approval of code and pipelines
• Environment Setup & Collaboration: Set up non-production and production environments including MFT flows, RBAC, cloud services, Git repositories, and defining appropriate branching strategies
• Design, test, and maintain scalable data architectures, including databases and distributed processing systems
• Collaborate with stakeholders including product owner(s), data science, and digital teams to assist with data-related technical issues, support data infrastructure needs and production release strategies
• Technical Leadership & Mentorship: Mentor and guide data engineers on best practices, business logic implementation, and quality assurance
• Identify and document technical debt
• differentiate between defects and scope changes and effectively communicate with product team
• Educate the organization both from IT (including vendors) and the business perspectives on data ingestion and data streaming tools, processes and best practices
• Establish strong relationship with vendor partners to ensure strong delivery, innovation and ongoing improvement in receiving high value services
• Provide technology or services ownership direction on all matters related to a key functional area – to associated functional lead and peers
• DevOps & Data Modeling: Lead deployment and transition-to-operations (TTO) activities for UAT and production
• Apply strong understanding of DevOps processes, Star Schema, Data Vault, and data warehousing principles

• 3-5 years of experience leading enterprise data warehouse development teams
• Proven success in Agile environments and cloud-based data platforms, especially Azure and Snowflake
• Expertise in building robust, scalable data pipelines for batch and streaming data
• Proficiency in SQL, Python, stored procedures, and scheduling tools
• Hands-on experience with ETL/ELT tools such as Azure Data Factory (ADF), Databricks, Snowflake, DBT and Talend
• Skilled in implementing monitoring and alerting mechanisms for data pipelines
• Strong capability in reviewing engineering deliverables for performance, scalability, and maintainability
• Experience with prompt engineering and leveraging Generative AI (GenAI) to accelerate development and automate engineering workflows
• Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related field
• Excellent communication, problem-solving, and analytical skills
• Proven leadership and mentoring capabilities
• Strong collaboration skills with cross-functional teams
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment
• Candidates must be eligible to work in the country of interest at the time any offer of employment is made and are responsible for obtaining any required work permits, visas, or other authorizations necessary for employment
• Prior to their start date, candidates will also need to provide proof of their eligibility to work in the country of interest

Based on equal qualifications, preference will be given to bilingual candidates