Brainway

Brainway is looking for a Senior Data Engineer to join a client project developing an AI-powered B2B platform.

You will help turn product data, customer data and external business data into reliable analytics that people can use to make decisions. Working with an existing product and analytics environment, you will develop data models, define meaningful metrics and deliver analytical features together with engineering and product teams.

This role combines hands-on data work with product thinking. You should be comfortable investigating unfamiliar datasets, asking what a metric actually means and following the work through to a useful, validated result.

What you will do

• Work with product and business stakeholders to turn questions into clear analytical requirements and measurable outcomes.
• Explore existing datasets, understand their business context and resolve inconsistencies in how data is interpreted.
•  Design analytical data models, write efficient SQL and build the transformations needed for reporting and product analytics.
•  Develop dashboards and customer-facing analytical features that make complex information easy to understand.
•  Define how new data sources should be integrated, including field mappings, transformation rules and acceptance checks.
•  Validate calculations and outputs, investigate discrepancies and improve data quality, performance and reliability.
•  Work with engineers on secure handling of customer data and appropriate access to analytical outputs.

•  Use AI-assisted tools to accelerate investigation and delivery while keeping results explainable, reproducible and checked.

   

What we are looking for

• 5+ years of relevant experience across data engineering, analytics engineering, BI or a closely related discipline.
• Strong SQL and practical experience designing data models and defining business metrics.
• Experience delivering dashboards or analytical products used in production.
• Hands-on experience with PostgreSQL, BigQuery or comparable relational and analytical platforms.
• A solid understanding of data transformation, integration and validation practices.
• The ability to work through incomplete requirements, ask useful questions and make sound product decisions.
• Clear communication with technical and non-technical stakeholders, including customers when needed.
• Confidence using AI tools alongside independent technical judgment and careful verification.
• Strong written and spoken English.
   

Useful additional experience

• Embedded analytics or customer-facing BI.
• Semantic layers, shared metric definitions, data governance or data-quality monitoring.
• Integrations with CRM, ERP, HRIS or other enterprise systems.
• APIs, Node.js or TypeScript.
• Version-controlled data and analytics workflows.

• Product analytics or analytics for enterprise operations.

   

Why this role

You will work at the intersection of engineering, analytics and product, with ownership of how business questions become dependable analytical capabilities. The work includes improving an existing foundation and helping shape how new data sources and analytical features fit into the product.
 

If you enjoy understanding the problem behind a report as much as building the data model behind it, we would like to hear from you.