Principal Data Engineer leading data strategy and platform architecture at AND Digital. Focusing on Snowflake implementation and client delivery for AI and analytics.
Responsibilities
Define and own the Snowflake architecture strategy for US clients - from ingestion to transformation and modelling.
Lead end-to-end design and implementation of Snowflake-based data platforms, ensuring scalability, performance, and security.
Establish best practices for schema design, query optimisation, and performance tuning within Snowflake.
Guide clients on Snowflake feature adoption (e.g. Snowpark, Streams, Tasks, Data Sharing, and Governance).
Ensure platforms are optimised for integration with downstream AI, analytics, and digital products.
Lead client-facing data engineering and strategy engagements, ensuring technical excellence and commercial success.
Oversee development of data pipelines and transformations feeding Snowflake environments.
Promote consistency in design patterns, CI/CD, and version control across teams and projects.
Drive operational excellence through measurable engineering standards and quality frameworks.
Work directly with senior client stakeholders to define data modernisation roadmaps and business outcomes.
Collaborate closely with AI, Product, and Cloud leads to align Snowflake data foundations with broader solution delivery.
Represent the data practice in proposals, workshops, and technical discovery sessions.
Mentor and develop data engineers and architects across US and nearshore teams.
Contribute to building AND Digital’s Snowflake delivery capability - frameworks, accelerators, and training.
Support business development and pre-sales conversations with Snowflake-aligned solution expertise (partner-sales alliances approaches put into practice).
Requirements
Proven experience designing and delivering Snowflake data platforms at scale.
Deep technical fluency in Snowflake architecture, data modelling, and SQL optimisation.
Strong understanding of data engineering best practices - ingestion, orchestration, transformation, and governance.
Demonstrated success in consulting or delivery-led environments, balancing technical rigour with client outcomes.
Experience leading cross-functional teams (data, AI, analytics) across multiple geographies.
Excellent communicator — credible with both technical and business stakeholders.
Minimum 2+ years in a leadership capacity within data or platform engineering.
8-12 years in data engineering or architecture, with at least 3 years focused on Snowflake.
Technical agnostic expertise, such as SQL, Python, and data orchestration tools (Airflow, dbt, or similar).
Understanding of how Snowflake underpins AI and analytics initiatives.
Experience managing distributed or nearshore data delivery teams.
Excellent problem-solving and client-facing skills.
Must reside on the East Coast (NY/NJ, Atlanta, or South Florida).
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