Full-Time Data Platform Engineer

We are seeking a skilled and experienced Data Platform Engineer to join our growing team.

Responsibilities:

• Design, implement, and maintain robust streaming and batch data pipelines using Databricks, Spark, and Python.
• Ensure data infrastructure is reliable, secure, and scalable, adhering to industry regulations and data governance standards.
• Monitor, troubleshoot, and proactively improve data infrastructure to ensure high availability and performance.
• Build and optimize data platforms and warehouses to meet the evolving needs of stakeholders across analytics, machine learning, and backend systems.
• Assist in the re-architecture of batch pipelines to streaming pipelines, ensuring real-time data flow for ML and operational needs.
• Collaborate with data scientists and analysts to streamline data processing for advanced analytics and machine learning.
• Establish and maintain MLOps workflows, ensuring seamless deployment, monitoring, and serving of ML models and features.
• Drive feature engineering and create systems to stage and serve features for machine learning.

You bring

• 5+ years of experience in data engineering or a similar role.
• Expertise in Apache Spark for large-scale data processing.
• Advanced knowledge of production-level Python
• Strong SQL skills for data manipulation and ETL processes.
• Experience with real-time streaming technologies such as Kafka or Kinesis.
• Familiarity with MLOps practices and workflows, including feature engineering, model training, and serving.

Preferred:

• Proficiency in Databricks for managing data pipelines and analytics workflows
• Infrastructure as Code (IaC), Terraform or AWS preferred
• Strong problem-solving skills and the ability to work collaboratively in cross-functional teams.
• An “act-like-an-owner” mentality with a bias toward taking action.

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