Data Consultant (Snowflake) - Contract

Your tasks

About the Role Our client is looking for a Data Engineer with strong hands-on experience in Snowflake to design, build, and maintain the pipelines and data models that our analysts, data scientists, and business teams rely on.

You will work closely with stakeholders to turn raw data from many sources into trusted, well-modelled datasets, and you will help shape our engineering standards as the platform grows.

• Design, build, and maintain scalable ETL/ELT pipelines to ingest data from databases, APIs, files, and streaming sources into Snowflake.
• Develop and optimize data models (dimensional, star/snowflake schemas, data vault where relevant) to support analytics and reporting.

• Write efficient, well-tested SQL and Python code for transformation and orchestration.
• Use Snowflake features such as Snowpipe, Streams and Tasks, Time Travel, Zero-Copy Cloning, Stored Procedures, and Dynamic Tables to build robust workflows.

• Monitor and tune Snowflake performance and cost, including warehouse sizing, clustering, query optimization, and resource monitors.
• Implement data quality checks, monitoring, alerting, and lineage so downstream users can trust the data.

• Apply data security and governance best practices, including role-based access control, masking policies, and data privacy compliance.
• Orchestrate and schedule workflows using tools such as Airflow, dbt, or equivalent.

• Collaborate with analysts, data scientists, product managers, and engineers to understand requirements and deliver the right solutions.
• Contribute to documentation, code reviews, CI/CD practices, and continuous improvement of the data platform.

Requirements

Required Qualifications

• 3 to 7 years of professional experience in data engineering or a closely related field.
• Strong hands-on experience with Snowflake, including data loading, performance tuning, and cost management.

• Advanced SQL skills, including complex joins, window functions, CTEs, and query optimization.
• Proficiency in Python (or a similar language such as Scala or Java) for data processing and automation.

• Solid understanding of data warehousing concepts, ETL/ELT patterns, and data modelling.
• Experience building and managing pipelines with orchestration tools such as Apache Airflow, Prefect, or Dagster.

• Experience with a major cloud platform (AWS, Azure, or GCP) and its storage and compute services (for example S3, ADLS, or GCS).
• Familiarity with version control (Git) and CI/CD workflows.

• Strong problem-solving skills and attention to detail.
• Good communication skills and the ability to work in a cross-functional team.