Employment: Full-time, permanent
Reporting to: CTO
The Role
We're looking for a Senior Data Engineer to take ownership of building, maintaining and improving the data ingestion pipelines that power mnAi's products.
You'll work with a wide range of data sources, including third-party APIs, web scraping, structured files and financial documents, transforming complex, inconsistent and often unstructured information into reliable, usable datasets.
This is a hands-on engineering role with significant autonomy. You'll be responsible for delivering data engineering projects from initial requirements through to production, including their ongoing reliability, performance and maintenance.
You'll work closely with the CTO to agree technical architecture, priorities and approaches, while having the freedom to make engineering decisions, challenge assumptions and recommend solutions.
What You'll Be Doing
- Design, build and maintain production-grade data ingestion and transformation pipelines using Python.
- Integrate data from third-party APIs, web scraping, CSV, Excel, JSON, PDFs and other structured or unstructured sources.
- Develop reliable extraction and processing workflows for complex documents, including financial statements and company information.
- Build reusable, maintainable components for data validation, transformation and enrichment.
- Work with PostgreSQL and Snowflake as our primary data storage and processing technologies.
- Develop and maintain integrations with OpenSearch and other supporting data services.
- Improve the efficiency, scalability and cost-effectiveness of existing pipelines.
Production Ownership & Data Quality
- Take responsibility for the reliability and quality of the pipelines you develop.
- Implement appropriate monitoring, logging, alerting and error handling.
- Identify and resolve data quality issues, including missing, duplicated, inconsistent or outdated records.
- Investigate production incidents, identify root causes and implement lasting fixes.
- Design pipelines that can recover from failures, safely retry operations and process data consistently.
- Maintain clear technical documentation and ensure systems can be understood and supported by others.
AI-First Development & Code Quality
- Use AI coding agents and assistants as a core part of your development workflow, including tools such as OpenAI, Claude and agentic development environments.
- Apply AI-assisted development to implementation, refactoring, debugging, testing and documentation.
- Critically review AI-generated code for correctness, maintainability, security, performance and suitability for production.
- Demonstrate strong code review skills, including identifying subtle bugs, architectural weaknesses and unnecessary complexity.
- Write and maintain meaningful automated tests to validate both code behaviour and data quality.
- Use appropriate open-source and proprietary AI models for data extraction, classification, enrichment and other processing tasks.
- Evaluate AI-assisted approaches pragmatically, balancing accuracy, reliability, cost and operational complexity.
Engineering Collaboration & Delivery
- Work with the CTO to agree technical architecture, priorities and delivery approaches.
- Break down complex engineering requirements into manageable, deliverable work.
- Provide realistic estimates, communicate progress and raise risks early.
- Participate in technical discussions, architecture reviews and peer code reviews.
- Take responsibility for delivering agreed work to a high standard, including deployment and ongoing support.
What We're Looking For
- Significant experience designing, building and maintaining data ingestion and ETL/ELT pipelines.
- Strong SQL skills and experience working with relational databases, particularly PostgreSQL.
- Strong experience with Snowflake and dbt, including data modelling, transformation, testing and optimisation.
- Experience integrating third-party APIs and processing data from multiple formats and sources.
- Strong automated testing, debugging and code review experience.
- Practical experience using AI coding assistants or agents as part of a professional development workflow.
- The ability to work independently, make sound technical decisions and take ownership of projects.
- Clear communication skills and a collaborative, pragmatic approach to engineering.
- AWS services such as S3, Lambda, ECS, RDS and Opensearch.
- Extracting structured information from PDFs and other complex documents.
- Docker, CI/CD pipelines and infrastructure automation.
- Integrating open-source or proprietary language models into production data workflows.
How We Work
We believe modern software engineering is increasingly about combining strong engineering fundamentals with effective AI-assisted development.
We encourage the use of AI agents to accelerate implementation, experimentation and problem-solving. However, speed alone isn't the goal.
We expect our engineers to understand the systems they're building, critically assess generated code and take responsibility for what reaches production.
We're a small engineering team, so ownership, communication and the ability to deliver independently matter more than rigid processes or job titles.
About mnAi
mnAi is a data and analytics business providing intelligence on companies, people and markets. Our platform brings together large volumes of information from diverse sources to support research, analysis and business decision-making.
Our engineering team builds and operates the systems responsible for collecting, processing, enriching and making that information accessible to our customers.
What We Offer
- Salary of £60,000–£80,000, depending on experience.
- Hybrid working options with a local office encouraging in person collaboration
- An inclusive environment where people are supported to do their best work
- The opportunity to take meaningful ownership of production data systems.
- Direct involvement in technical decisions and the evolution of our data platform.
- Access to modern AI development tools and the freedom to use them effectively.
- A small, collaborative engineering team with minimal bureaucracy.
- Opportunities to develop your technical expertise and influence engineering practices.
