Senior Data Platform Architect

Snowflake1 months ago

Location

GB-London

Type

Full Time

Level

Senior

Role

Data Platform Architect

Posted

Jan 30, 2026

Full TimeSenior

The role

Summary

Snowflake is seeking a Senior Data Platform Architect to join their Applied Field Engineering team in London, providing technical leadership to design Snowflake's Cloud Data Platform architecture for enterprise customers. This role combines 10+ years of data architecture experience with 5+ years of pre-sales expertise, requiring deep technical knowledge of modern data technologies including SQL, Python, Spark, and cloud data platforms while working directly with sales teams to drive customer success and business growth.

What you'll do

Technical Leadership: Provide technical leadership in designing Snowflake Cloud Data Platform architecture as part of enterprise data ecosystems

Customer Engagement: Work directly with sales teams to understand customer needs and strategize winning sales cycles

Value Demonstrations: Deliver compelling value-based demonstrations showcasing Snowflake's capabilities across data ingestion, transformation, and lakehouse workloads

Proof of Concepts: Support enterprise Proof of Concepts from initial demo through design and implementation phases

Executive Presentations: Present Snowflake technology and vision to executives and technical contributors at strategic prospects, customers, and partners

Hands-on Technical Work: Work hands-on with prospects and customers throughout the entire sales cycle demonstrating technical value

Market Intelligence: Maintain deep understanding of competitive and complementary technologies and positioning strategies

Cross-functional Collaboration: Collaborate with Product Management, Engineering, and Marketing teams to improve products and marketing strategies

What we look for

Technical

Data Architecture Experience10+ years of architecture and data engineering experience within Enterprise Data space

Pre-sales Experience5+ years experience in pre-sales environment as Sales Engineer, Solutions Engineer, or Solutions Architect

Database TechnologiesBroad experience with large-scale Database, Data Warehouse technology, ETL, analytics and cloud technologies

Programming SkillsHands-on development experience with SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive and Big Data technologies

Data IntegrationDeep understanding of data integration services and ETL/ELT pipeline tools like Apache NiFi, Matillion, Fivetran, Qlik, Informatica

Streaming TechnologiesFamiliarity with streaming technologies including Kafka, Flink, Spark Streaming, Kinesis and real-time use cases

Lakehouse ArchitectureExperience designing interoperable data lakehouse architectures and working with Iceberg, Delta, and Parquet

Education

Bachelor's DegreeBachelor's Degree required in any field

Advanced Degree PreferredMaster's Degree in computer science, engineering, mathematics or related fields preferred, or equivalent experience

Experience

Enterprise Data ExperienceMinimum 10 years of hands-on experience in enterprise data architecture and engineering

Pre-sales Technical RoleMinimum 5 years in customer-facing pre-sales technical roles

Executive PresentationProven track record of presenting to both technical and executive audiences

Customer DiscoveryAbility to perform deep discovery of customer architecture frameworks and connect with data solutions

Skills

Required skills

SQLAdvanced SQL skills for complex data operations and querying

PythonProficient Python programming for data engineering and automation

Apache SparkHands-on experience with Spark ecosystem including PySpark

Data ArchitectureDeep expertise in designing enterprise-scale data architectures

ETL/ELT PipelinesExperience building and optimizing data integration pipelines

Presentation SkillsOutstanding presentation abilities for technical and executive audiences

Cloud PlatformsMulti-cloud data platform experience and expertise

Pre-sales ExperienceProven track record in technical pre-sales and customer-facing roles

Nice to have

Streaming TechnologiesExperience with Kafka, Flink, Spark Streaming, or Kinesis

Data Integration ToolsHands-on experience with Apache NiFi, Matillion, Fivetran, Qlik, or Informatica

Lakehouse FormatsWorking knowledge of Iceberg, Delta Lake, and Parquet formats

Hadoop EcosystemExperience with Hadoop, Hive, and related big data technologies

Real-time ProcessingUnderstanding of CDC and near real-time data processing use cases

Advanced DegreeMaster's degree in computer science, engineering, mathematics or related field

Compensation & benefits

Benefits

Career Development

Opportunities to build big, move fast, and take technology and careers to the next level

Innovation Culture

Culture focused on impact, innovation, and collaboration

Growth Opportunities

Fast-growing company with scaling team and accelerated growth opportunities

Professional Impact

Opportunity to make significant impact in cloud computing and data platform space

Interview process

1
Initial Screening — Phone or video screening with talent acquisition to assess basic qualifications and cultural fit
2
Technical Assessment — Technical discussion covering data architecture experience, pre-sales background, and hands-on technology skills
3
Presentation Round — Demonstration of presentation skills through technical demo or architectural whiteboarding session
4
Customer Scenario — Case study or role-play scenario simulating customer interaction and solution design
5
Final Interviews — Final round interviews with hiring manager and key stakeholders including potential team members