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

Summary

Build and maintain ETL/ELT pipelines, data models, and curated datasets across Snowflake, Databricks, and cloud platforms while supporting ML/AI and LLM solutions. Requires Python, SQL, data engineering experience, a bachelor’s or master’s degree in a related field, and at least 5 years in a similar role.

Responsibilities

Develop, test, and maintain ETL/ELT pipelines; implement web scraping solutions; optimise data workload performance and cost; apply data modelling standards; contribute to cloud data architecture; support ML/AI and LLM productionisation; expose curated datasets; follow data governance and security practices; partner with stakeholders; contribute to code reviews, documentation, testing, and CI/CD

Qualifications

Bachelor’s or master’s degree in computer science, Statistics, Mathematics or related; at least 5 years of experience in a similar role; strong programming in Python and SQL; collaborative problem solver with strong communication skills

Education requirements

Bachelor’s or master’s degree in computer science, Statistics, Mathematics or related

Experience requirements

At least 5 years of experience in a similar role

Benefits

Private Health Insurance; Performance Bonus; Training & Development; Hybrid Working Model