AI ML Data Engineer

l Design, build, and maintain scalable, secure, and high-performance batch and streaming data pipelines using modern data engineering practices. l Lead the modernization and migration of on-premise data platforms to cloud-native architectures, overseeing infrastructure, networking, security, and deployment pipelines. l Develop and maintain core data platform components that support reliable ingestion, transformation, enrichment, and consumption of enterprise data assets. l Collaborate with data domain experts across various departments to understand data sources and design efficient, connected data models. l Ensure data accuracy, quality, relevance, and governance by implementing validation, monitoring, documentation, and security controls. l Analyze large datasets to identify trends, patterns, and actionable insights; perform data analysis to support analytics and AI use cases. l Enable reporting and analytics by making curated, trusted datasets available to BI and downstream consumers. l Partner with AI/ML Engineers to design, build, and improve machine learning models and AI-powered enterprise applications. l Optimize data and AI pipelines for scalability, performance, reliability, and cost efficiency in production environments. l Mentor and guide engineers and interns, contributing to skill development in data engineering and AI/ML. l Collaborate effectively with cross-functional teams and stakeholders, communicating complex technical concepts clearly

l Experience Required: 10+ Years with Databricks, ADF,SQL l We are seeking a highly skilled Senior Data Engineer with a strong focus on data engineering and experience in AI/ML solutions. l The ideal candidate will have a proven track record in building and maintaining data pipelines, data models, and data integration workflows., l 5+ years of experience in software development with a strong focus on Data Engineering. l 1+ years of experience delivering solutions that include AI ML or Generator components. l Proven experience building and maintaining ML Pipelines, Data Modelling, and Data Integration workflows. l Strong Basic SQL skills for querying, transformation, and performance optimization. l Advanced proficiency in Python and experience with Scala for data and AI workloads. l Hands-on experience with Spark (batch and streaming), Databricks, SparkSQL, and Cloud Platforms. l Experience with Azure IaaS, cloud infrastructure, monitoring, and deployment automation. l Experience with Continuous Integration and Continuous Delivery (CI/CD), version control, and CI CD & DevOps practices (Git, GitHub Actions, Jenkins OpenSource) PREFERRED SKILLS: l Experience with Databricks ML, Databricks, and Agentic AI solutions. l Knowledge of MDM, Data Governance, and data governance frameworks. l Experience in healthcare, insurance, or regulated industries. l Familiarity with Intersystems HealthShare, HL7 reporting standards, and healthcare data standards. l Experience with Terraform, Infra as code, and Robotic Process Automation. l Azure Databricks certifications. l Expertise You’ll Bring: Strong stakeholder management and cross-functional collaboration skills. l Knowledge of data security, privacy, and Enterprise Architecture best practices. l Proven success delivering master data, analytics, or AI-enabled data products using Azure Databricks, Snowflake, and cloud platforms. l Experience with Data Governance, MDM, Data Mesh, and regulated environments is highly valued.