Azure Data Engineer (Databricks)

Quick Facts

• Role: Azure Data Engineer (Databricks)

Description

Design, build, and maintain scalable data processing solutions on Azure, leveraging Databricks and Azure Data Factory. You will develop robust data pipelines that integrate structured and unstructured data from databases, APIs, and streaming platforms. You’ll collaborate with cross-functional teams to deliver end-to-end data platform solutions and document work with performance and cost considerations.

Responsibilities

• Develop scalable data processing solutions on Azure for large structured and unstructured datasets

• Design, build, and maintain data pipelines integrating diverse sources (databases, APIs, streaming)

• Collaborate with data engineers, data scientists, and cloud architects on end-to-end data platforms

• Work with business analysts, source system experts, data architects, engineers, and product owners across project stages

• Communicate and document technical work, considering performance and cost

Requirements

• Hands-on experience implementing data lake and pipeline solutions (Databricks, Azure Data Factory)

• Proven experience designing and implementing solutions in Azure cloud

• Proficiency in SQL

• Experience with PySpark

• Data modeling experience (3NF, star/snowflake schemas)

• ELT/ETL design pattern experience (including Azure Data Factory)

• Experience with Python (or similar scripting languages) for transformation, orchestration, and automation

• Familiarity with Databricks advanced features (Unity Catalog, MLflow, Jobs & Pipelines)

• Understanding of cloud data architecture principles (Lakehouse, Medallion, API integration, event-driven architecture)

• CI/CD and DevOps experience for data workflows (Git, Azure DevOps)

• Analytics integration experience (e.g., Power BI)

• Excellent communication and client-facing skills

• Strong collaboration across multidisciplinary teams

Benefits

• Permanent employment contract

• People Lead support with a defined professional development path and coaching

• Wide training package (soft/technical/language; e-learning; Gallup test; GenAI training; co-financing certifications)

• Employee Assistance Program (legal, financial, psychological consultations)

• Eligibility for Employee Share Purchase Plan and quarterly dividends

• Paid employee referral program

• Private medical care and life insurance

• Access to Worksmile platform (Multisport and additional benefits)

Role notes

Flexible work model: mostly remote, with some onsite/in-person time depending on project needs.