Data Engineer (Python) - Remote

Role Overview We offer a flexible working policy that supports a healthy balance between personal and professional well‑being. This role requires in‑office presence on Tuesdays and Thursdays to collaborate, connect, and learn from peers – while also maintaining the flexibility for meaningful work‑life balance. Responsibilities Design, develop and maintain scalable data pipelines on Databricks and Microsoft Azure to ingest and transform large volumes of structured and unstructured data from multiple sources. Build and optimize large‑scale data workflows for normalization, deduplication, enrichment, and quality enforcement. Architect and manage data platforms that enforce governance, lineage tracking, and access controls across the organization. Implement automated data validation and quality monitoring to ensure accuracy, consistency, and reliability across datasets. Support AI and ML teams by preparing clean, well‑documented datasets and building reliable data interfaces for model development and evaluation workflows. Maintain data lineage and follow data privacy, security and governance best practices across the lakehouse. Collaborate with applied AI, analytics and product teams to understand data requirements and translate them into scalable engineering solutions. Qualifications Bachelor's degree or higher in Computer Science, Data Engineering, Applied Mathematics or a related quantitative field. 4+ years of data engineering experience with a strong track record delivering production‑grade pipelines at scale. Strong proficiency in Python, PySpark and Spark SQL for large‑scale data processing. Hands‑on experience with Databricks, including Delta Lake, Delta Live Tables, Unity Catalog, Volumes and Databricks Workflows. Solid understanding of lakehouse architecture principles, including Medallion architecture, and experience designing for reliability, performance and governance. Experience orchestrating data pipelines on cloud infrastructure, preferably Microsoft Azure and Databricks. Strong sense of ownership over data quality and platform reliability. Preferred Experience Experience with Microsoft Azure services including Azure Data Lake Storage, Azure AI Foundry, Azure ML and Microsoft Fabric. Familiarity with AI or ML workflows and experience supporting data needs for model training, fine‑tuning or evaluation. Experience with data processing, including text normalization, embeddings or semantic search datasets. Experience with large document datasets. Experience working with data in the legal domain. Prior work designing architectures for large‑scale document or text corpora. Equal Opportunity Statement iManage provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, lay‑off, recall, transfer, leaves of absence, compensation and training. #J-18808-Ljbffr iManage