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