Data Principal

Join AND, a leader in the data industry, as a Data Principal. In this pivotal role, you will lead the local Data & AI Practice, expand our data capability, and drive growth and value for our clients. You will work closely with AND's global data practice team, your practice team, and local leadership. You should have strong expertise in data, a willingness to keep learning, and a passion for producing high-quality work that delivers real value.

• Lead the local Data & AI Practice, expanding the company's data capabilities and strengthening its position in the data industry.
• Manage and inspire teams, navigating the complexities of enterprise-scale problem solving and turning challenges into opportunities for clients.
• Champion relationships with technology partners, working collaboratively to deliver high-quality data solutions for clients.
• You bring strong expertise in your craft, alongside a willingness to keep learning
• You’re comfortable navigating ambiguity and solving complex problems collaboratively
• You value low-ego collaboration and enjoy working as part of multidisciplinary teams
• You communicate clearly and build trust quickly with clients and teammates
• You’re pragmatic, adaptable and outcome-focused
• You enjoy sharing knowledge and helping others grow
• You care deeply about producing high-quality work that delivers real value
• Data Leadership: You have a proven track record of managing and inspiring teams. You excel at navigating the complexities of enterprise-scale problem solving, turning challenges into opportunities for our clients
• Designing for People and Purpose: Your expertise goes beyond just building scalable architectures; you design systems with a focus on delivering value. You ensure that your extensible and scalable solutions are implemented because they consistently meet the evolving needs of both the business and its users
• Stakeholder Artistry: You are a master of client-facing delivery. You can translate complex data concepts into business value, managing multi-vendor environments with a focus on long-term partnership
• Industry Stewardship: You are a lifelong learner who keeps a pulse on industry standards and best practices
• Partnership Focus: You champion relationships with technology partners, whether established or new, working collaboratively to deliver for clients
• Quality Advocate: You take personal pride in the integrity of your work. Beyond just fixing bugs, you champion quality assurance and performance tuning as a mindset, ensuring the data programs we build for our clients are robust, reliable, and respected
• Hands on mindset: You speak the language of data fluently, whether it's Python, R, or SQL and are ready to jump in to provide solutions where required
• Data capabilities: You understand the full lifecycle of data from data discovery, storage, pipelines, ETL, streaming through to how data is managed including data quality, metadata management and how data is used for applications and core decision making through advanced analytics
• You lead by example. While your primary focus is strategic, you maintain the technical depth required to guide teams through the full Data Product Lifecycle:
• Data Product mentality: You understand how to build Data Products ensuring that every pipeline and dataset is discoverable, addressable, and secure by design
• Technology breadth: You bring a seasoned perspective to both modern and traditional ecosystems—with extensive experience building data solutions using Microsoft Azure and/or AWS native services, with development to production experience in Snowflake, Databricks or Fabric, managing delivery with an Agile mindset
• AI: You have a deep expertise or experience of AI, specifically how to build AI solutions in modern data platforms (Databricks/Snowflake). In addition to Microsoft Azure, leveraging core technologies in the AI Foundry ecosystem, understanding different business challenges require varied solutions from SLM’s to intelligent Agentic automation from LLM foundational models, Human in the Loop and MLOps
• Data Architecture Design: You understand and know when to use the following data architecture design patterns RAG (Retrieval-Augmented-Generation), Serverless, DWH models, Data Mesh and Data Products