Principal Engineer – Data Platforms & MLOps (Databricks)

<div><span><h1><strong>Principal Engineer – Data Platforms &amp; MLOps (Databricks)</strong></h1><h3><br></h3><p style="margin-bottom:0cm;"><strong>Company Overview&nbsp;</strong><br>At Codvo, software and people transformations go hand-in-hand. We are a global empathy-led technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day.</p><p style="margin-bottom:0cm;">We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.</p><h3><strong>Role Overview</strong></h3><div>We are looking for a <strong>hands-on Principal Engineer</strong> with deep expertise in <strong>Databricks</strong> to design, build, and scale enterprise-grade data platforms and MLOps pipelines. You will be the technical authority on how enterprises adopt and maximize Databricks — from ingestion to governance to machine learning deployment — and a mentor who raises the bar for engineering excellence.</div><hr><h3><strong>Key Responsibilities</strong></h3><ul><li><strong>Platform Architecture</strong>: Design and implement end-to-end data architectures on <strong>Databricks Lakehouse</strong>, covering ingestion, transformation, storage, and analytics.</li><li><strong>Pipelines &amp; Workflows</strong>: Build and optimize <strong>ETL/ELT pipelines</strong> with <strong>Delta Live Tables</strong>, <strong>Spark Structured Streaming</strong>, and workflow orchestration.</li><li><strong>Governance &amp; Security</strong>: Implement <strong>Unity Catalog</strong>, fine-grained access controls, and compliance frameworks across enterprise data estates.</li><li><strong>MLOps at Scale</strong>: Operationalize ML models using <strong>MLflow</strong>, <strong>Model Registry</strong>, and CI/CD pipelines integrated with cloud DevOps tools.</li><li><strong>Performance &amp; Cost Optimization</strong>: Tune Databricks clusters, jobs, and workflows for <strong>scale, speed, and efficiency</strong> across multi-cloud deployments.</li><li><strong>Client Advisory</strong>: Work closely with enterprise stakeholders to provide <strong>best practices, reference architectures, and accelerators</strong> tailored to their use cases.</li><li><strong>Mentorship &amp; Standards</strong>: Guide engineers in Databricks best practices, enforce coding standards, and lead design/code reviews.</li></ul><hr><h3><strong>Qualifications</strong></h3><ul><li><strong>8+ years</strong> in large-scale <strong>data engineering / platform engineering</strong>, with <strong>3+ years hands-on Databricks</strong> experience.</li><li>Deep expertise in:<ul><li><strong>Databricks Lakehouse Platform</strong> (Delta Lake, Delta Live Tables, Databricks SQL).</li><li><strong>Governance &amp; Security</strong> with <strong>Unity Catalog</strong>.</li><li><strong>MLOps with MLflow</strong> and model lifecycle management.</li></ul></li><li>Strong programming skills in <strong>PySpark, SQL, Python</strong>; experience with <strong>Scala</strong> a plus.</li><li>Hands-on with <strong>cloud integration</strong> (AWS, Azure, or GCP) and DevOps pipelines (Terraform, GitHub Actions, Azure DevOps, etc.).</li><li>Proven track record of <strong>building and scaling Databricks workloads in production</strong> for enterprise clients.</li></ul><div>&nbsp;</div></span></div>