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Data Generalist Job CarePay
IT Jobs, CarePay Jobs.
The Data Generalist is an individual contributor in the Data team, operating across the full data lifecycle. In a small, highly autonomous team, this role focuses primarily on data engineering and backend engineering, with some involvement in data science and analytics engineering, emphasizing end-to-end delivery, stakeholder impact and continuous learning.
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Data Engineering & Backend Engineering
- Maintain and improve the data infrastructure using Snowflake, AWS, Terraform and Kubernetes, always keeping in mind reliability, security and cost
- Orchestrate, refactor and troubleshoot
ETL pipelines in Airflow - Develop FastAPI microservices that expose the data products, from simple reports to advanced rules-based and ML systems
- Monitor data quality alerts and raise occurring issues to other development teams
- Collaborate with the Head of Data on architectural decisions and technical improvements
Analytics Engineering & Data Modelling
- Build and maintain analytics models using dbt, following best practices such as star schemas and dimensional modelling
- Adapt ETL pipelines to evolving data models
- Ensure analytical datasets are reliable, well-documented, and optimised for self-service BI and downstream consumption
- Occasionally work on ad-hoc analyses and customer-facing dashboards
Machine Learning & Advanced Analytics
- Design, build, and productionise machine learning models
- Develop user-facing ML and AI products and proof-of-concepts using tools such as scikit-learn, LLMs, Streamlit and FastAPI
Collaboration & Mentorship
- Actively collaborate with other Data team members through pairing sessions and informal mentorship
- Share best practices across data, backend and ML engineering
- Reach out to other technical leads to clarify backend logic, data semantics, or system behaviour required for data initiatives
Ownership & Stakeholder Interaction
- Lead data projects end-to-end with minimal supervision, from requirements gathering to delivery
- Proactively spot opportunities for improvements in the data infrastructure and ML/AI adoption
- Understand and articulate trade-offs between technical solutions, delivery speed, and stakeholder needs
- Translate complex technical concepts into clear, business-oriented language
- Occasionally present and explain data products, insights, and deliveries directly to stakeholders
Requirements
- 3+ years of experience in a data-related role
- Proficiency in Python, SQL, dbt and Airflow
- Experience building, maintaining, and documenting APIs in Python (preferably FastAPI)
- Familiarity with modern DevOps practices – Cloud (AWS preferred), IaC (Terraform), CI/CD, Kubernetes
- Familiarity with data science/ML concepts
- Strong curiosity and willingness to learn
- Good understanding of data tooling landscape, ability to pick a right tool for the job while keeping a pragmatic mindset
- Nice to have: Some experience with LLMs/Agentic AI, Streamlit, Frontend development
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How to Apply
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