Senior Data Governance Engineer - Azure & Databricks Expert

Responsibilities 

• Design and implement scalable forecasting and predictive analytics models to solve complex business challenges across multiple domains. 

• Develop and optimize data models (logical, physical, dimensional, and semantic) to support analytics, ML, and reporting use cases. 

• Work with large, complex datasets from multiple sources—cleansing, transforming, and preparing them for analytical consumption. 

• Build, train, and evaluate ML models using statistical and machine learning techniques to enhance accuracy, performance, and interpretability. 

• Collaborate with data engineers and cloud teams to integrate ML pipelines into AWS or Azure environments using modern ETL and orchestration tools. 

• Translate business objectives into technical data solutions and actionable insights through strong analytical reasoning and stakeholder communication. 

• Ensure data quality, lineage, and consistency through standardized data definitions, metadata documentation, and model versioning practices. 

• Continuously improve models through retraining, drift detection, and performance monitoring using MLOps best practices. 

Required Skills and Experience 

• Proven expertise in machine learning and statistical modeling for forecasting, demand prediction, or time-series analysis. 

• Strong data modeling skills across dimensional, relational, and semantic structures. 

• Advanced proficiency in Python for data wrangling, feature engineering, and ML model development (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow preferred). 

• Intermediate SQL skills with experience writing efficient queries and optimizing database performance. 

• Strong analytical and problem-solving mindset with the ability to derive insights and communicate outcomes to technical and business stakeholders. 

Preferred Skill Sets: