Senior AI Data Engineer, End-to-End Data Platforms

Analog Devices, Inc.; Limerick; On-site; EUR 120,000 - 180,000; Full time

Job summary

Analog Devices, Inc. in Ireland is seeking a Staff AI Data Engineer to lead the design and delivery of scalable data and AI solutions from ingestion to production. You will architect lakehouse platforms, implement GenAI workflows, and mentor engineers while aligning with senior stakeholders on data-driven outcomes.

The role emphasizes cloud/data platform expertise (Databricks, Snowflake), MLOps, and strong Python/SQL skills to build enterprise-grade data products and governance.

Qualifications

• 10+ years of software/data engineering experience, including data engineering and AI/GenAI production work.
• Degree in Computer Science, Electrical Engineering, Data Science, or related field.
• First-principles understanding of distributed systems, streaming, and data engineering fundamentals.

Responsibilities

• Architect and deliver end-to-end data and AI solutions for scalable, production-grade systems.
• Design modern data platforms on lakehouse architectures and cloud data warehouses.
• Deploy AI/GenAI solutions including RAG, vector search, and agent orchestration; guide lifecycle from prototype to production.
• Lead DataOps/LLMOps foundations: experiment tracking, evaluation, monitoring, and cost guardrails.
• Mentor engineers and communicate data-driven insights to senior stakeholders.

Skills

Distributed systems

Data engineering

Python

SQL

Spark

MLOps/LLMOps

Education

Bachelor's degree in Computer Science, Electrical Engineering, or related field

10+ years of software/data engineering experience

Tools

Databricks

Snowflake

Airflow

Docker

Kubernetes

PowerBI/Tableau

Job description

Analog Devices, Inc. in Ireland is seeking a Staff AI Data Engineer to lead the design and delivery of scalable data and AI solutions from ingestion to production. You will architect lakehouse platforms, implement GenAI workflows, and mentor engineers while aligning with senior stakeholders on data-driven outcomes.

The role emphasizes cloud/data platform expertise (Databricks, Snowflake), MLOps, and strong Python/SQL skills to build enterprise-grade data products and governance.