Snowflake Data Engineer

Position Title:
Snowflake Data Engineer
Organisation / Function:
Data & AI Practice

Job Summary / Purpose
We are seeking an accomplished and detail-oriented Snowflake Data Engineer to join our
Data & AI practice. The successful candidate will bring deep expertise in data engineering,
ETL/ELT pipelines, and cloud-native data platforms, with a strong focus on Snowflake. This
role is critical in building and optimising modern data ecosystems that enable data-driven
decision making, advanced analytics, and AI capabilities for our clients.
As a trusted practitioner, you will collaborate with architects, developers, and analysts to
design, implement, and maintain secure and high-performing data pipelines. You will thrive
in a collaborative, client-facing environment, with a passion for solving complex data
challenges, driving innovation, and ensuring the seamless delivery of data solutions.

Primary Responsibilities
 Client Engagement & Delivery
 Data Pipeline Development (Batch and Streaming)
 Snowflake & Cloud Data Platforms
 Data Architecture & Modelling
 Collaboration & Best Practices
 Quality, Governance & Security

Business Relationships
 Solution Architects
 Data Engineers, Developers, ML Engineers and Analysts
 Client stakeholders up to Head of Data Engineering, Chief Data Architect, and Analytics
leadership

Competencies / Critical Skills
Key Competencies
 Proven experience in data engineering and pipeline development on Snowflake and
cloud-native platforms.

 Strong consulting values with ability to collaborate effectively in client-facing
environments.
 Hands-on expertise across the data lifecycle: ingestion, transformation, modelling,
governance, and consumption.
 Strong problem-solving, analytical, and communication skills.
 Experience leading or mentoring teams of engineers to deliver high-quality scalable
data solutions.
Technical Expertise
 Deep expertise with Snowflake features (warehouses, Snowpark, data sharing,
performance tuning).
 Proficiency in ETL/ELT tools such as DBT, Matillion, Talend, or equivalent.
 Strong SQL and Python (or equivalent language) skills for data manipulation and
automation.
 Hands-on experience with cloud platforms (AWS, Azure, GCP).
 Knowledge of data modelling methodologies (star schemas, Data Vault, Kimball, Inmon).
 Familiarity with data lake architectures and distributed processing frameworks (e.g.,
Spark, Hadoop).
 Experience with version control tools (GitHub, Bitbucket) and CI/CD pipelines.
 Understanding of data governance, security, and compliance frameworks.
 Exposure to AI/ML workloads desirable.

Experience, Qualifications, and Education
 Experience: Minimum 5–8 years in data engineering, data warehousing, or data
architecture roles, with at least 3+ years working with Snowflake.
 Education: University degree required.
 Preferred: BSc/MSc in Computer Science, Data Engineering, or related field
 Snowflake certifications (SnowPro Core, Advanced) highly desirable.

Measures of Success
 Delivery of high-performing, scalable, and secure data pipelines aligned to client
requirements.
 High client satisfaction and successful adoption of Snowflake-based solutions.
 Demonstrated ability to innovate and improve data engineering practices.
 Contribution to the growth of the practice through reusable assets, accelerators, and
technical leadership.