Data & AI Engineer

📋 Description

• Design, develop, and optimize scalable ETL/ELT pipelines using Databricks, Apache Spark, and Delta
• Build robust workflows for processing structured and unstructured data, automating ingestion
• Tune Spark jobs and data processing workflows to improve latency, throughput, scalability, and
• Collaborate with machine learning engineers and data scientists to operationalize AI models within
• Implement automated deployment pipelines and Infrastructure-as-Code practices using tools such as
• Establish and maintain data access controls, security policies, and governance standards using

🎯 Requirements

• At least three years of experience in cloud-native data engineering, including a minimum of two
• Strong proficiency in Python, SQL, and Spark-based frameworks, with experience designing and
• Practical experience building data architectures across cloud environments and implementing modern
• Familiarity with MLflow and the processes required to track, version, deploy, and operationalize
• Experience implementing CI/CD pipelines and Infrastructure-as-Code solutions using Terraform
• An active Databricks Certified Data Engineer Associate or Professional certification, or Databricks

🎁 Benefits

• Remote-First Work: The flexibility to work remotely while collaborating with a globally connected
• Collaborative Environment: The opportunity to work alongside skilled professionals in a supportive
• Technical Growth: Exposure to modern Lakehouse architectures, cloud platforms, data engineering
• Meaningful Client Impact: The opportunity to build scalable, production-ready solutions that
• Inclusive Workplace: A culture that values diversity, equal opportunity, collaboration, curiosity