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Data Engineer
KIData Engineer building production-grade pipelines, data models, and MLOps infrastructure for Ki’s algorithmic insurance platform. Collaborating with actuaries, data scientists, and engineers to scale commercial performance insights.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in software engineering with a strong focus on Python for API development and data engineering, alongside expertise in cloud platforms like GCP and AWS. Demonstrates capability in designing scalable data solutions, managing data governance, and collaborating effectively in agile environments.
Highest-signal resume keywords
Python API DevelopmentData EngineeringCloud Platforms (GCP/AWS)Infrastructure as Code (IAC)Data Modelling and Governance
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Software EngineeringData Pipeline DevelopmentETL/ELT ProcessesData Quality ManagementAPI Development (FastAPI/Flask)Database Management (PostgreSQL/MySQL/BigQuery)CI/CD PipelinesData Governance Best PracticesSystem DesignData Architecture
Soft Skills
CollaborationCuriosityAdaptabilityEnthusiasm
Industry Keywords
MLOpsAgile MethodologyData Asset ManagementExposure ManagementPortfolio Management
Tech Stack
Tools & technologiesAWSBigQueryCloudETLFlaskGoogle Cloud PlatformMySQLPostgresPython
About the role
Key responsibilities & impact- Monitor the commercial performance of Ki’s algorithmically underwritten insurance business in real time
- Upgrade algorithm decision-data capture from database logging to a versioned event stream with purpose-built views for customer use cases
- Work with actuaries, data scientists, and engineers to design, build, optimise, and maintain production-grade data pipelines feeding the Ki algorithm
- Evaluate and integrate new internal and external data sources
- Design and engineer data models and supporting infrastructure with data architects for growth and scale
- Create frameworks, infrastructure, and systems to manage and govern Ki’s data asset
- Develop data and MLOps capability infrastructure with the broader Engineering community
- Collaborate in an agile, cross-functional squad with stakeholders and consumers of the systems
Requirements
What you’ll need- Strong experience in software engineering, with proficiency in a language such as Python for API development, data engineering, and automation tasks
- Experience with storage solutions such as PostgreSQL, MySQL, and BigQuery
- Experience in API development using FastAPI or Flask
- Solid knowledge of cloud platforms, specifically GCP and/or AWS, with ability to design and deploy data solutions at scale
- Experience with Infrastructure as Code (IAC) and CI/CD pipelines
- Understanding of data modelling, ETL/ELT processes, data quality, and data governance best practices
- Ability to collaborate with Exposure Management, Portfolio Management, and Data Science stakeholders
- Curiosity, adaptability, and enthusiasm for an agile, squad-based environment
- Desirable: experience with large, complex, and siloed data estates and simplifying and streamlining processes
- Desirable: foundation in system design and ability to architect scalable, maintainable, and resilient data systems
Benefits
Comp & perks- Highly competitive remuneration and benefits package
- Remuneration and benefits package kept under constant review
- Recognition and rewards for extraordinary effort by teams or individuals
- Initial recruiter screening call
- Interview with hiring manager
- Technical interview
- Values interview