Data and AI Engineer

Job description

As a data & AI engineer you will contribute across the end-to-end data development lifecycle for data ingestion, cleansing, validation, transformation, curation and presentation. Reporting to the principal data & AI, 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 ATOM’s customers and stakeholders.

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.

Requirements

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, SQL, etc.
• 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 related.
• 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