Snowflake Data Engineer

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:

• 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 (Git Hub, 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 (Snow Pro 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.

We’re a business with a global reach that empowers local teams, and we undertake hugely exciting work that is genuinely changing the world. Our advanced portfolio of consulting, applications, business process, cloud, and infrastructure services will allow you to achieve great things by working with brilliant colleagues, and clients, on exciting…