At a Glance
- Tasks: Lead innovative data solutions and collaborate with clients to unlock data value.
- Company: Join a top-tier tech firm known for excellence in analytics and AI.
- Benefits: Enjoy competitive pay, health perks, remote work options, and growth opportunities.
- Other info: Dynamic role with excellent career advancement and learning opportunities.
- Why this job: Shape the future of data-driven decisions in high-stakes environments.
- Qualifications: Experience in data engineering and Snowflake implementation is essential.
The predicted salary is between 72000 - 88000 £ per year.
Location: London; UK
Work type: Hybrid
Seniority: Senior
Primary skill: Data Software Engineering
Posted: 2026-11-02
When data platforms are pushed to their limits, only the most robust solutions stand up to the challenge. The Senior Snowflake Consultant role in London is part of a practice recognized for building solutions that set the standard in analytics and artificial intelligence. Demand from clients continues to accelerate as organizations seek to unlock value from their data at scale. This growth is driven by the proven impact and technical depth of the Data practice, which consistently delivers results in complex enterprise environments. The person in this role shapes how data-driven decisions are made in high-stakes settings.
Responsibilities
- Collaborate with clients to understand business goals, data requirements and success measures
- Lead technical discovery and translate complex requirements into scalable data platform and AI-ready solutions
- Design, develop and implement Snowflake solutions, including data modelling, performance tuning and secure access patterns
- Rapidly prototype and de-risk high-stakes initiatives by turning ambiguous problems into working technical solutions
- Architect and deliver end-to-end pipelines and data products across ingestion, transformation, orchestration and consumption layers
- Embed directly with client/EPAM engineering teams to co-develop production-grade pipelines and platform components
- Implement governance, security and compliance best practices, including RBAC, masking, auditing and data access controls
- Engage senior stakeholders to drive decisions, trade-offs, prioritisation and delivery alignment
- Lead delivery teams to ensure quality, timelines and client satisfaction across engagements
- Support account growth through opportunity identification, solution shaping, estimation, proposals and client presentations
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering or a related discipline, or equivalent practical experience
- Extensive experience in data engineering, analytics engineering or data platform delivery in consulting or professional services environments
- Proven hands-on Snowflake implementation expertise across architecture, ELT patterns, data modelling and performance optimisation
- Strong experience with cloud platforms (AWS, Azure and/or GCP) and cloud-native data services
- Strong understanding of data governance and security in enterprise environments, including access control and privacy requirements
- Demonstrated ability to take solutions from prototype to production with operational readiness and reliability in mind
- Excellent problem-solving skills and the ability to work effectively with ambiguous requirements and evolving priorities
- Strong stakeholder management skills, with the ability to influence and communicate credibly at senior levels
- Experience leading delivery teams and coordinating cross-functional contributors to deliver outcomes
- Strong commercial awareness, including experience contributing to scoping, estimation and proposal development
Nice to have
- Snowflake ecosystem experience with tools such as dbt, Airflow/Dagster, Matillion/Fivetran, Kafka/Kinesis/Event Hubs or similar
- Experience with Snowflake capabilities such as Snowpark, Streams & Tasks, Dynamic Tables, Data Sharing or Iceberg tables, CoCo, CoWork, Cortex Analyst and Search and Semantic Views
- Experience enabling ML/AI workloads through feature-ready datasets, governed access patterns and collaboration with MLOps teams
- CI/CD and DevOps practices for data, including Git-based workflows, automated testing and environment promotion
- Familiarity with cost management and performance optimisation practices in cloud data platforms
- Snowflake and other cloud certifications (AWS, Azure or GCP)
- Experience in forward-deployed, solutions engineering or high-intensity client delivery environments
We offer
- EPAM Employee Stock Purchase Plan (ESPP)
- Protection benefits including life assurance, income protection and critical illness cover
- Private medical insurance and dental care
- Employee Assistance Program
- Competitive group pension plan
- Cyclescheme, Techscheme and season ticket loans
- Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
- Learning and development opportunities including in-house training and coaching, professional certifications, and courses
- If otherwise eligible, participation in the discretionary annual bonus program
- If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program
*All benefits and perks are subject to certain eligibility requirements
Senior Snowflake Consultant - Data & AI Engineering employer: EPAM Systems
Join a dynamic and innovative team in London where your expertise as a Delivery Director will be valued and nurtured. We pride ourselves on a collaborative work culture that fosters continuous improvement and professional growth, offering you the chance to work alongside award-winning teams in the Retail/Consumer Products industry. With a focus on client satisfaction and strategic project delivery, you'll find meaningful and rewarding employment in an environment that champions creativity and technical excellence.
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We think this is how you could land Senior Snowflake Consultant - Data & AI Engineering
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We think you need these skills to ace Senior Snowflake Consultant - Data & AI Engineering
Some tips for your application 🫡
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
