Data Engineer role specializing in Azure & Snowflake at InfoCentric. Leading design and delivery of enterprise - scale data platforms for large organizations.
About the role
- Data Engineer developing and maintaining scalable data platforms at Vintage Cash Cow. Collaborating with teams to ensure accurate and reliable data for decision making.
Responsibilities
- Build and maintain a modern, scalable data platform that supports growth and decision-making.
- Ensure data is accurate, consistent, and trusted across the business.
- Improve speed, reliability, and automation of data pipelines and reporting workflows.
- Enable high-quality self-serve analytics by delivering well-modelled, well-documented data sets.
- Support digital performance and CRM insight through strong marketing data foundations.
- Design, implement, and maintain robust data pipelines across multiple systems.
- Ensure smooth, well-governed flow of data from source → warehouse → BI layers.
- Support end-to-end warehouse design and modelling as our stack grows.
- Integrate and manage a wide range of data sources within Snowflake.
- Build automated checks to monitor accuracy, completeness, and freshness.
- Run regular audits and troubleshoot issues quickly and calmly.
- Identify opportunities to streamline pipelines, improve performance, and reduce cost.
- Work closely with teams across Growth, Finance, Ops, and Product to understand KPIs and reporting needs.
- Document architecture, pipelines, models, and workflows so everything is clear and easy to pick up.
Requirements
- Strong Snowflake experience: loading, querying, optimising, and building views/stored procedures.
- Solid SQL skills: confident writing complex queries over large datasets.
- Hands-on pipeline experience using tools like dbt, FiveTran, Airflow, Coalesce, HighTouch, Rudderstack, Snowplow, or similar.
- Data warehousing know-how and a clear view of what “good” looks like for scalable architecture.
- Analytical, detail-focused mindset: you care about quality, reliability, and root-cause fixes.
- Great communication: able to explain technical concepts in a simple, useful way.
- Comfortable working in a small, high-impact team where you’ll shape the roadmap.
- Experience working with HubSpot data (ETL into a warehouse, understanding the schema, reporting context) is nice to have.
- Digital marketing analytics background: ads platforms, attribution, funnel performance, campaign measurement is nice to have.
- Familiarity with CRMs/marketing automation tools (HubSpot, Marketo, Salesforce, etc.) is nice to have.
- Python or R for automation, data wrangling, or pipeline support is nice to have.
- Understanding of A/B testing or experimentation frameworks is nice to have.
- Exposure to modern data governance/catalogue tooling is nice to have.
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