Data Engineer responsible for building reliable ETL/ELT workflows using Azure and Python. Collaborating with teams to deliver clean, structured data and modernize cloud platforms.
About the role
- 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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