Sr. ML Data Engineer (ETL) | TELECOMMUTE

Senior Data Engineer With ML Feature Engineering Expertise100% TELECOMMUTEWe seek a talented Senior Data Engineer with ML feature engineering expertise to join our Consumer ML team. This role involves designing and implementing advanced feature engineering and ETL pipelines to enable robust machine learning applications. The ideal candidate has hands-on experience with Databricks, a deep understanding of the medallion architecture, and a proven track record of supporting the end-to-end ML lifecycle. Experience with MLflow and an aptitude for creating data-driven insights are highly desirable.Responsibilities:Feature Engineering Data Integration Develop and maintain feature engineering pipelines using Databricks to support ML models effectivelyData Pipeline Development Integrate diverse data sources eg clickstreams user behaviour demographic data to create user behaviour features profiles for complex ML tasksMedallion Architecture Design and implement ETL, ELT pipelines aligned with the bronze silver and gold layers of the medallion architectureModel Support Build data pipelines to support ML model training calibration and deployment leveraging MLflow for experiment tracking and performance monitoringQuery Optimization Low Latency Pipelines Design low latency production ready data pipelines to support real-time and batch model inferenceCICD Practices Apply CICD principles for seamless pipeline deploymentData Governance Ensure pipelines comply with security and regulatory standards particularly for handling PII and maintain metadata and master data across the data catalogueCollaboration Work closely with ml scientists ml engineers and other stakeholders to align data transformation with business objectivesQualifications:7 years in data engineering and at least 4 years focusing on ML feature engineering ETL pipeline development and data preparation for MLProven experience managing pipelines on Databricks using Apache Spark with a strong understanding of the medallion architectureFamiliarity with ML lifecycle management with MLflow experience as a strong plus and advanced skills in Apache Spark PySpark for big data processing and analyticsProficient in Python for data manipulation and SQL for query optimizationExperience building pipelines for real-time and batch model serving in production environments and knowledge of CICD practices for ETLELT pipeline developmentExpertise in metadata and master data management within technical data cataloguesUnderstanding of data security and compliance especially with sensitive data like PIIMandatory Skills: Apache Spark, Databricks, Java, Python, Scala, SparkSQLRequired Skills: Machine LearningBasic Qualification:Additional Skills:This is a high PRIORITY requisition.