We are seeking a strategic and experienced Team Lead/Director of Data Analytics to lead the design and execution of enterprise-wide analytics initiatives for our client. The role will oversee all aspects of delivery and architecture of the modern data platform and collaborate with clients, executive stakeholders, and technology teams to champion the adoption of analytics solutions that generate meaningful insights, enhance operational effectiveness, ensure adherence to regulatory standards, and foster innovation that benefits both customers and internal teams.
Requirements
- Develop and lead the overall vision for enterprise analytics, aligning initiatives with organizational objectives, compliance standards, and customer expectations;
- Convert strategic business priorities into actionable plans across data engineering, reporting & business intelligence, AI/ML, and advanced analytics functions;
- Serve as a champion for analytics-driven decision making, building executive support and securing necessary investments;
- Participate in cross-functional leadership groups to influence enterprise-wide technology strategies and business roadmaps from a data and analytics perspective;
- Direct and nurture a high-performing analytics organization, including Data Engineering, BI, Data Science enablement, and Governance functions;
- Cultivate a high-accountability environment that emphasizes technical excellence, innovation, and continuous professional development;
- Oversee talent acquisition, retention strategies, and performance management across the analytics team;
- Manage and optimize the analytics operating budget, including headcount, platforms, and cloud infrastructure, ensuring resource allocation aligns with strategic outcomes;
- Collaborate closely with Finance to maintain budget discipline, manage vendor relationships, and transparently report value delivered relative to investment;
- Monitor and forecast usage-based cloud expenses (e.g., Azure Databricks, Data Factory, storage, licensing), proactively adjusting to balance performance and cost-effectiveness;
- Lead the architecture and continuous enhancement of a cloud-native data platform, leveraging tools such as Azure Data Factory, Databricks (Python, SQL), dbt, and Power BI;
- Promote and operationalize medallion architecture principles (bronze/silver/gold layers) for scalable and efficient data processing;
- Define and implement data modeling standards (e.g. dimensional modeling for analytics, transactional schema for OLTP), ensuring cross-platform integration;
- Drive infrastructure automation and repeatability via Infrastructure-as-Code practices using tools like Terraform;
- Integrate advanced data governance tools (e.g. Unity Catalog, Microsoft Purview) to manage data lineage, security, and role-based access;
- Lead prioritization and execution of analytics initiatives, ensuring alignment with business goals and timely delivery;
- Embed Agile frameworks to improve team velocity, stakeholder feedback loops, and the delivery of tangible outcomes each sprint;
- Uphold engineering excellence by institutionalizing standards around source control (Git/GitHub), CI/CD, peer reviews, and automated testing;
- Oversee development and release of analytics solutions for internal and external users, ensuring accuracy, usability, and timely delivery;
- Ensure all analytics solutions comply with applicable regulations in financial services, including privacy, reporting, and risk management standards;
- Implement strict controls to protect Sensitive Personally Identifiable Information (SPII) and ensure adherence to frameworks such as PCI DSS and SOC;
- Establish governance policies and stewardship practices across structured and unstructured data assets;
- Serve as the executive accountable for ensuring data privacy and security within the analytics domain, including incident response;
- Lead efforts to ensure the organization is equipped for secure data collaboration, including external integrations and data sharing frameworks;
- Maintain a forward-looking perspective, staying updated on emerging trends such as open table formats, real-time analytics, AI copilots, and regulatory technology, and translating these developments into practical strategies;
- Position analytics as a core enabler of customer satisfaction, operational efficiency, and compliance leadership;
- Apply DevOps principles and DataOps practices to streamline data warehouse development and deployment;
- Prepare and optimize the analytics platform to support machine learning, AI-driven insights, and real-time data processing;
- Willing to participate in on-call rotations as needed for operational support;
- Ability to apply DevOps principles and DataOps practices to streamline data warehouse development and deployment;
- Ability to prepare and optimize the analytics platform to support machine learning, AI-driven insights, and real-time data processing;
- Ability to lead efforts to ensure the organization is equipped for secure data collaboration, including external integrations and data sharing frameworks;
- Ability to maintain a forward-looking perspective, staying updated on emerging trends such as open table formats, real-time analytics, AI copilots, and regulatory technology, and translating these developments into practical strategies;
- Ability to position analytics as a core enabler of customer satisfaction, operational efficiency, and compliance leadership;
- Willing to participate in on-call rotations as needed for operational support;
Benefits
- Competitive compensation package
- Growth opportunities
- Modern tech stack
