Sr Snowflake Data Engineer

Senior Data Engineer
This is a senior-level role focused on the design, development, and ownership of data solutions built primarily on Snowflake Data Cloud. You will lead the architecture and implementation of scalable data pipelines, establish robust data models, and enforce data governance and security standards across the platform.
Key Responsibilities
Data Pipeline & Engineering

• Design, build, and own scalable data pipelines and ingestion processes using SQL, Python, dbt, and cloud-native tools.
• Architect and implement ELT/ETL patterns across batch, incremental, and CDC pipelines.
• Lead the development of data models using Dimensional Modeling, Data Vault, or Lakehouse approaches.
• Define and implement data transformation logic, data quality validations, and business rules.

Platform & Cloud Engineering

• Own the design and optimization of Snowflake environments, including warehouse sizing, cost governance, storage standards, schema management, and performance tuning.
• Work with cloud platforms (AWS, Azure, or Google Cloud Platform) to integrate with Snowflake and deliver high-performance, cost-efficient solutions.
• Lead pipeline orchestration using Airflow, dbt Cloud, or similar tools.

Governance & Security

• Establish and enforce data governance frameworks, access controls, and security protocols- with particular focus on Snowflake-native capabilities such as row-level security, dynamic data masking, and data sharing.
• Define and maintain data quality standards, lineage documentation, and compliance requirements.

Requirements

• 7+ years of hands-on experience in data engineering, with a strong professional track record in place of formal credentials.
• Proven, deep expertise with Snowflake- including performance optimisation, cost management, security features, and data architecture.
• Snowflake certification 
• Solid working knowledge of SQL and at least one scripting language, preferably Python.
• Experience designing and building ELT/ETL pipelines across batch, incremental, and CDC patterns.
• Familiarity with data modeling approaches such as Dimensional Modeling, Data Vault, or Lakehouse.
• Experience with at least one cloud platform (AWS, Azure, or Google Cloud Platform) in a data engineering context.

Nice to Have

• Hands-on experience with dbt, Airflow, or dbt Cloud.
• Exposure to data governance frameworks and security best practices within cloud environments.
• Experience working in a consultancy or multi-client environment.

Work Authorization:
Candidates must be authorized to work in the United States without current or future visa sponsorship. Unfortunately, we are unable to sponsor visas for this position at this time.