Senior Data Engineer

Vatix is a fast-growing SaaS company founded in London and Kraków in 2019, focused on Governance, Risk, and Compliance software, particularly Health & Safety and Operational Excellence. Their platform serves over 800 businesses and government organizations worldwide, including Cambridge University, Siemens, and Intel. The company works with a diverse product suite spanning web applications, mobile apps, IoT-enabled safety devices, and data platforms.

• Strong SQL and hands-on experience with modern cloud data warehouses such as Redshift, BigQuery, Snowflake.
• Solid understanding of ETL/ELT, CDC, and data pipeline design.
• Strong relational data modelling skills with awareness of performance, cost, and scale.
• Proficiency in Python for scripting, automation, and data handling.
• Comfortable with JSON, structured and semi-structured schemas, and querying APIs.
• Experience building data products or dashboards for internal/external users.
• Practice of ownership: driving data work end-to-end with sound judgement on trade-offs.
• Openness to AI-enabled SDLC, using AI as a tool, not a replacement for engineering judgement.
• Curiosity about emerging data tooling.
• Excellent English communication skills, able to explain complex data concepts to technical and non-technical audiences.

Nice to have:

• Experience in B2B/enterprise SaaS, especially security, compliance, or data-heavy products.
• Experience with embedded analytics or BI tooling.
• Experience with AWS data services (Redshift, Glue, Athena, S3, Lambda) and Infrastructure as Code (Terraform).
• STEM degree or equivalent practical experience.

Data Infrastructure and Ownership:

• Own and evolve the AWS-based data warehouse, including Postgres RDS replicated into Redshift via Zero-ETL.
• Keep replication, models, and transformations reliable, secure, and performant, owning them in production.
• Build and maintain data infrastructure powering customer-facing dashboards.
• Own the technical data backlog, deciding what to build, in what order, and why.
• Get involved early in product and architecture decisions, choosing appropriate data models and storage.
• Replace manual and reactive work with well-designed systems and automation.

Integration and Collaboration:

• Work with Product and Engineering to embed analytics ensuring data segregation per customer.
• Lead cross-cutting data and integration projects to enable engineering focus.
• Design inbound API for third-party systems pushing event data, handling authentication, field mapping, idempotency, and validation.
• Build and maintain data integrations with systems like HubSpot, including connectors, APIs, and automation.

Standards and Quality:

• Set technical direction and standards for data at Vatix.
• Collaborate with the data team to share best practices and uphold standards.
• Act as guardrail for AI-generated models and pipelines: interrogate logic, validate numbers, and strengthen pipelines before release.

Work Methodology:

• Design before implementation.
• Continuous integration and quality assurance before shipping.
• Small, frequent releases.
• Follow Scrum and retrospectives.