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Senior Snowflake Consultant - Data & AI Engineering

Pay
Pay not listed
Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
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Employment
Not stated

What you’ll work on

Full posting
  • Lead technical discovery and translate requirements into data platform solutions

  • Design and implement Snowflake solutions, including modelling and performance tuning

  • Architect and deliver end-to-end data pipelines and data products

  • Implement RBAC, masking, auditing and other data access controls

  • Lead delivery teams to keep quality, timelines and client satisfaction on track

From the employer’s posting
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
Architect and deliver end-to-end pipelines and data products across ingestion, transformation, orchestration and consumption layers
Implement governance, security and compliance best practices, including RBAC, masking, auditing and data access controls
Lead delivery teams to ensure quality, timelines and client satisfaction across engagements

Tools in this posting

  • AWS
  • Azure
  • dbt
  • Fivetran
  • GCP
  • Iceberg
  • Kafka
  • Snowflake
  • Airflow
  • Dagster
Source — Tool mentions in context
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

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Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 2, 20261 day ago
Recorded sightings
3
Last seen by us
Nov 4, 2026

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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
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UK

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