About the Role
As a Data & AI Engineer, you will contribute across the end-to-end data development lifecycle, focusing on data ingestion, cleansing, validation, transformation, curation, and presentation. You will work within a talented team of data engineers to deliver high-impact, secure data and AI solutions that support the ambitious goals of customers and stakeholders.
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Hands-on Engineering & Delivery
- Develop, test, and maintain robust ETL/ELT pipelines to ingest and transform data from multiple sources into the data lake and data marts.
- Implement robust web scraping solutions.
- Optimise performance and cost of data workloads (partitioning, compression, query tuning, etc).
Data Modelling & Platform Contribution
- Apply data modelling standards (dimensional models, star/snowflake schemas, canonical data models) to support reporting, analytics, and AI/ML use cases.
- Contribute to the evolution of the cloud data architecture under the guidance of the Principal Data & AI.
Analytics, BI, ML & AI Enablement
- Work with data scientists, ML engineers, and analytics teams to support the productionisation of ML/AI and LLM-based solutions through reliable data pipelines and feature stores.
- Expose curated, well-documented datasets to enable self-service reporting, dashboards, and analytical tools.
Quality, Governance & Security
- Follow data governance, data quality, and metadata management practices across the platform.
- Apply security best practices (IAM roles and policies, encryption at rest and in transit, row/column-level security, auditing and monitoring).
Collaboration & Ways of Working
- Partner with product, engineering, and business stakeholders to understand data requirements and translate them into scalable technical solutions.
- Contribute to code reviews, documentation, testing, and DevOps/CI-CD practices, adhering to clean code, reusable components, version control, and observability standards.
Knowledge and Skills
- Hands-on experience as a data engineer with focus on Snowflake, Databricks, Azure, GCP and/or AWS platforms.
- Strong programming skills in Python, SQL, and other relevant languages.
- Proven experience in developing ETL/ELT pipelines using various technologies, including but not limited to AWS Glue, dbt, Informatica, Talend, Python, and SQL.
- Working knowledge of SAP HANA / SAP HANA Cloud data modelling, XS Engine, Calculation Views, SDI/SDA is a strong plus.
- Experience with analytical frontend tools (e.g. MicroStrategy, Power BI, Tableau, Spotfire, SAP Analytics Cloud).
- Exposure to Large Language Models, generative AI, and intelligent agents, including hands-on experience building Agentic AI workflows and automations using tools such as n8n, LangChain / LangGraph, Make (Integromat), Zapier AI, CrewAI, or similar orchestration frameworks.
- Experience delivering CI/CD and DevOps capabilities in a data environment.
- A bachelor’s or master’s degree in computer science, Statistics, Mathematics or a related field.
- A collaborative, proactive problem solver with strong communication skills and the ability to work effectively across diverse teams.
- At minimum 5 years of experience in a similar role.
Benefits
- Work in an international environment
- Innovation in FinTech
- Private Health Insurance
- Hybrid Working Model
- Training & Development
- Performance Bonus
