About this role

Design, build, and optimize ETL/ELT data pipelines using Azure and GCP services
Develop and maintain optimized data models within multi-cloud data warehouse solutions
Monitor and optimize the performance of data warehouse queries
Collaborate with Data Scientists to design feature stores and pipelines for ML models
Implement workflows to automate the end-to-end data lifecycle for AI/ML processes
Work with Data Science teams to deploy and manage machine learning models in production environments
Write complex SQL queries and develop scripts in Python for data manipulation

Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative field
4+ years of professional experience in a Data Engineering, Software Engineering, or Data Architecture role
Expertise in major Azure services (Blob Storage, Data Factory, Databricks, Synapse) and/or GCP services (Cloud Storage, BigQuery, Dataflow)
Expert in SQL and modern ELT methodologies
Experience with BI tools like Power BI or Looker
Advanced proficiency in Python
Familiarity with ML lifecycle tools
Expertise in applying security controls
Familiarity with infrastructure as code (IaC) practices using Terraform or cloud-native tooling

Specialist Engineer – Data

Key skills