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Atom Technology

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Data And AI Engineer

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Summary

Builds and maintains end-to-end data pipelines (ETL/ELT), data models, and secure cloud data platforms while enabling ML/AI and LLM-based solutions. Core stack: Python, SQL, Snowflake, Databricks, AWS/Azure/GCP, plus agentic AI tooling like LangChain and n8n.

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.

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, Mathematicsor 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.
  • Work in an international environment
  • Innovation in FinTech
  • Private Health Insurance
  • Hybrid Working Model
  • Training & Development
  • Performance Bonus

Requirements:

Skills

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