Senior Data Engineer: Snowflake & Lakehouse Architect

Vivanti Consulting; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Mentoring Program

360° Progress Reviews

Guilds & Regular Training

Paid Certifications

Hackathons & Innovation Days

Kudos & Recognition Programs

Socials & Team Days

Job summary

Vivanti Consulting seeks a skilled Principal Data Engineer to architect and deliver scalable data pipelines and lakehouse solutions. You will own complex data ecosystems, partner with analysts and ML engineers, and drive governance, security and cost optimisation across cloud platforms.

You’ll leverage Snowflake, Spark and Delta Lake to implement robust data architectures, mentor peers, and contribute to continuous learning and certification programs. London-based hybrid work offered.

Qualifications

• 7+ years of experience building scalable data pipelines in Snowflake/Spark/Python.
• Experience with data governance, lifecycle management and data platform architectures.
• Strong problem solving, critical thinking and collaboration skills.

Responsibilities

• Designing and building robust data pipelines using Snowflake, Spark, and Delta Lake.
• Implementing scalable and secure Lakehouse architectures on Snowflake.
• Collaborating with analysts, ML engineers, and platform teams to deliver Snowflake-native solutions.
• Applying best practices in data governance, CI/CD, and orchestration within the Snowflake ecosystem.
• Ensuring systems are secure, reliable and cost-effective.

Skills

Python

Spark

SQL

Cloud platforms (Azure, AWS, GCP)

Data modelling (Inmon, Data Vault, Kim

Tools

Snowflake

Spark

Delta Lake

Airflow

dbt

Fivetran

Terraform

Job description

Vivanti Consulting seeks a skilled Principal Data Engineer to architect and deliver scalable data pipelines and lakehouse solutions. You will own complex data ecosystems, partner with analysts and ML engineers, and drive governance, security and cost optimisation across cloud platforms.

You’ll leverage Snowflake, Spark and Delta Lake to implement robust data architectures, mentor peers, and contribute to continuous learning and certification programs. London-based hybrid work offered.