Senior Data Software Engineer

We are looking for a Senior Data Software Engineer to join our team. This role sits at the heart of how data-driven insights are built, delivered, and scaled across the organization. You'll partner with skilled professionals across multiple disciplines to bring innovative solutions to complex challenges. It's a great opportunity for someone who enjoys combining strong engineering practices with a passion for data-driven decision making.

Responsibilities

• Support and take part in preparing machine learning datasets and managing scoring processes
• Build and maintain deep familiarity with real-time and snapshot-based data sources company-wide, along with the Analytics team members who own them
• Partner with Data Scientists to build and roll out key machine learning models
• Advance the ML component of the Enterprise Data Platform strategy, expanding how ML predictions and recommendations are distributed through API-based scoring and data warehouse access
• Embed automated workflows into ML Data Engineering processes to support monitoring and alerting
• Apply performance tuning techniques and optimize query execution
• Serve as a go-to resource for the Machine Learning team on matters related to Data Lifecycle Management
• Stay current with evolving technologies across databases, data lakes, and data warehouse platforms
• Work alongside Analytics team members to follow documented architecture, design, and deployment standards, ensuring policy compliance
• Architect and build scalable, reusable data models

Requirements

• Bachelor's or Master's degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related field
• 3+ years of hands-on, relevant professional experience
• Background in Machine Learning, Data Engineering, ML Infrastructure, or similar areas, with a solid foundation in probability, statistics, and machine learning concepts
• Hands-on experience with Databricks, including Unity Catalog, along with cloud ML platforms such as Azure ML Studio, AWS, or GCP
• Experience building and scaling end-to-end ML systems, ETL/ELT pipelines, and data workflows using Python, NumPy, Pandas, and SQL
• Experience developing scalable APIs and microservices with FastAPI, alongside Snowflake or comparable data warehouse technologies
• Strong communication and cross-functional collaboration skills, with working English fluency at B2 level or higher, supporting clear understanding of business requirements

Nice to have

• Experience deploying production workloads using Docker and Kubernetes, with a solid grasp of scalable, reliable software engineering practices
• Familiarity with Microsoft Azure for building and managing cloud-based solutions