Snowflake Data Engineer

hackajob is collaborating with NTT DATA UK to connect them with exceptional tech professionals for this role.

Snowflake Data Engineer

Data & AI Practice

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 optimizing 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.

• 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

• 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.

• 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:

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.

• 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.