V
Lead Software Engineer
Job Description
Job Requirements
Snowflake and dbt Engineers – Data Product Factory Experience: 8+ years Role Type: Senior Data Engineering / Data Products Role Overview We are seeking experienced Snowflake and dbt Engineers to build reusable, governed, and analytics-ready data products for the regulatory data platform.The engineers will work within a data product factory model, delivering scalable pipelines, transformation logic, data models, quality controls,documentation, and automated deployments. Design, develop, test, and deploy Snowflake data products and reusable data pipelines. Build scalable ELT transformations using dbt Core or dbt Cloud. Develop dbt models, macros, packages, snapshots, seeds, tests, documentation, and exposures. Implement dimensional, Data Vault, star schema, and other analytical data models. Design Snowflake databases, schemas, stages, file formats, streams, tasks, views, and stored procedures. Ingest data from APIs, files, databases, RIM platforms, and enterprise applications.Implement incremental processing, CDC, slowly changing dimensions, and efficient data-loading patterns. Develop automated data-quality, reconciliation, completeness, uniqueness, and referential-integrity checks. Implement data lineage, metadata, documentation, and data contracts. Optimise Snowflake performance, warehouse usage, query execution, and cost. Support secure data access using roles, policies, masking, row-level security, and encryption.
7-10Years
Snowflake and dbt Engineers – Data Product Factory Experience: 8+ years Role Type: Senior Data Engineering / Data Products Role Overview We are seeking experienced Snowflake and dbt Engineers to build reusable, governed, and analytics-ready data products for the regulatory data platform.The engineers will work within a data product factory model, delivering scalable pipelines, transformation logic, data models, quality controls,documentation, and automated deployments. Design, develop, test, and deploy Snowflake data products and reusable data pipelines. Build scalable ELT transformations using dbt Core or dbt Cloud. Develop dbt models, macros, packages, snapshots, seeds, tests, documentation, and exposures. Implement dimensional, Data Vault, star schema, and other analytical data models. Design Snowflake databases, schemas, stages, file formats, streams, tasks, views, and stored procedures. Ingest data from APIs, files, databases, RIM platforms, and enterprise applications.Implement incremental processing, CDC, slowly changing dimensions, and efficient data-loading patterns. Develop automated data-quality, reconciliation, completeness, uniqueness, and referential-integrity checks. Implement data lineage, metadata, documentation, and data contracts. Optimise Snowflake performance, warehouse usage, query execution, and cost. Support secure data access using roles, policies, masking, row-level security, and encryption.
- Implement CI/CD pipelines using GitHub, GitHub Actions, Azure DevOps, or equivalent. Collaborate with Data Architects, Regulatory Data Leads, MDM, AI, and business stakeholders. Support production deployment, monitoring, incident resolution, and continuous improvement. Required Skills and Experience 8+ years of experience in data engineering, cloud data platforms, or data warehouse development. Strong hands-on experience with Snowflake and dbt. Advanced SQL and strong experience with data modelling and ELT development. Experience with Python, APIs, cloud storage, orchestration, and data integration. Knowledge of Snowflake security, performance optimisation, resource monitoring, and cost management. Experience with data quality, reconciliation, lineage, governance, and regulated data.Strong knowledge of Git, CI/CD, testing, code review, and deployment automation. Experience working in Agile data product or platform engineering teams.
7-10Years
More Info
Key Skills
deployment automation
CI CD
ELT development
data quality reconciliation
lineage governance
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