Senior Data Engineer (Snowflake - 6 Month FTC)

AND Digital Limited; West of England; On-site; GBP 90,000 - 130,000; Full time

Job summary

AND Digital Limited is seeking an experienced Lead / Senior Data Engineer in the United Kingdom to architect, build and deploy modern data pipelines using Snowflake, dbt and Dagster. You will design scalable data models, ML models, and own governance, security and data quality across the stack.

The role emphasizes technical leadership, agile delivery, and collaboration with product managers, analytics leads, and platform architects.

Qualifications

• Hands-on experience architecting modern data pipelines in Snowflake/dbt/Dagster.
• Proven ability to model data and ML solutions at scale.
• Experience with ML lifecycle within Snowflake is a plus.
• Knowledge of data security, RBAC and data masking.

Responsibilities

• Own data pipeline architecture from ingestion to marts.
• Lead design of scalable data models and ML models.
• Ensure governance, security, and automated quality tests.
• Collaborate with product, analytics, and platform teams.
• Champion CI/CD and version control best practices.

Skills

Data Modeling

Machine Learning

Leadership

Agile Delivery

Data Governance

Data Security

Unit/Integration Testing

Data Quality

Tools

Snowflake

dbt

Dagster

SQL

Python

CI/CD tooling

Git

Workflow orchestration

Job description

• We are seeking an experienced Lead / Senior Data Engineer. In this role, you will take hands‑on ownership of architecting, building, and deploying modern data pipelines in Snowflake, dbt and Dagster
• You will lead the designing of scalable data models and machine learning models
• Pipeline & Architecture Ownership: Design and implement automated, modular transformation pipelines in a modern cloud data warehouse, following a clean, tiered physical data architecture (from raw ingestion to governed marts)
• Experience with machine learning models - Needs experience with ML development life cycle within Snowflake (Martech experience highly desirable)
• Governance & Security: Implement enterprise‑grade data security standards, including automated quality testing, role‑based access control (RBAC), and dynamic data masking for sensitive customer information (PII)
• Technical Leadership: Guide engineering best practices across CI/CD, version control, and automated orchestration, collaborating closely with product managers, analytics leads, and platform architects

• Data Quality & Governance: Hands‑on experience establishing automated unit/integration test suites, lineage tracking, and role‑based privacy controls
• Complex Data Modeling(dbt): Demonstrated track record modeling in dbt
• Transformation & Orchestration: Advanced SQL and Python engineering skills with deep experience in modern data transformation frameworks and workflow DAG orchestrators
• Agile Delivery: Experience working in fast‑paced sprint cadences, breaking down complex epics into clear, shippable increments
• Cloud Data Platforms: Proven expertise in architecting and operating data solutions within enterprise cloud data warehouses (e.g., modern columnar cloud platforms)