Job Title

Platform Engineer Lead (Azure & Databricks)Location: 100% RemoteJob Type: Full-time Role OverviewWe are seeking a highly experienced Platform Engineer Lead with deep expertise in cloud architecture, specifically within Microsoft Azure and Databricks ecosystems. This role requires a hands-on technical leader who can design, build, and scale enterprise-grade data and platform solutions while mentoring engineering teams and driving best practices across the organization.Key ResponsibilitiesLead the design and implementation of scalable, secure, and high-performance cloud-based platforms on Azure.Architect and manage Databricks-based data platforms, including data ingestion, transformation, and analytics layers.Define and enforce platform engineering standards, governance, and best practices across teams.Collaborate with cross-functional stakeholders including Data Engineering, DevOps, Security, and Business teams to align platform capabilities with business objectives.Drive cloud-native architecture patterns such as microservices, event-driven systems, and distributed data processing.Oversee CI/CD pipelines, infrastructure as code (IaC), and automation using tools like Terraform, ARM templates, or Bicep.Ensure platform reliability, scalability, and performance through proactive monitoring, logging, and optimization strategies.Mentor and lead a team of engineers, providing technical direction, code reviews, and career guidance.Evaluate and integrate new technologies to enhance platform capabilities and efficiency.Ensure compliance with security, data governance, and regulatory requirements.Required Skills & Experience10+ years of overall IT experience with at least 3–5 years in a Lead role.Strong expertise in cloud architecture, with a focus on Microsoft Azure services (e.g., Azure Data Factory, ADLS, Synapse, AKS).Extensive hands-on experience with Databricks, including Spark optimization, Delta Lake, and performance tuning.Proven experience designing and implementing enterprise data platforms and distributed systems.Strong understanding of data engineering concepts, ETL/ELT pipelines, and big data processing frameworks.Experience with DevOps practices, CI/CD pipelines, and Infrastructure as Code (Terraform, ARM, etc.).Proficiency in programming languages such as Python, Scala, or SQL.Experience with monitoring and observability tools (e.g., Azure Monitor, Log Analytics).Solid understanding of security best practices in cloud environments (IAM, networking, data protection).