Databricks Resident Data Architect

Accountabilities: Serve as a dedicated Resident Data Architect and trusted technical advisor, supporting strategic customer initiatives and ensuring successful adoption of modern data solutions.

Lead the architecture, design, implementation, and optimization of enterprise-scale data platforms using Databricks Lakehouse technologies.

Partner with business stakeholders, technical teams, and leadership to define data strategies, technology roadmaps, and transformation initiatives.

Design scalable lakehouse architectures while ensuring best practices across data engineering, governance, security, performance, and reliability.

Drive data modernization, cloud migration, and digital transformation programs across complex enterprise environments.

Guide engineering teams on data modeling, ETL/ELT processes, analytics architecture, and production deployment practices.

Support the adoption of AI/ML capabilities, real-time analytics, and advanced data solutions within modern data ecosystems.

Establish and improve CI/CD processes, MLOps practices, and operational frameworks for production data workloads.

Provide technical leadership, mentorship, and knowledge sharing to customer teams and delivery partners.

Manage project delivery, identify risks, communicate progress, and ensure alignment between technical solutions and business objectives.

Requirements

10+ years of experience in consulting, client-facing technology engagements, with at least 7 years focused on data engineering, analytics, and modern data platforms.

Proven experience delivering multiple enterprise Databricks implementations, including hands-on architecture and development responsibilities.

Advanced expertise in the Databricks Lakehouse Platform, Apache Spark, Delta Lake, and distributed data processing concepts.

Databricks Certified Data Engineer Professional certification or equivalent advanced certification is required.

Strong experience with at least one major cloud platform such as AWS, Azure, or GCP, with familiarity across multiple cloud environments.

Solid understanding of data architecture, data integration, governance, security, quality frameworks, and performance optimization.

Experience implementing CI/CD pipelines, production deployment processes, and modern engineering practices.

Knowledge of MLOps principles, AI/ML implementation workflows, and operationalizing machine learning solutions is preferred.

Familiarity with Databricks Unity Catalog, data governance frameworks, and visualization platforms such as Power BI or Tableau is an advantage.

Strong stakeholder management, communication, and consulting skills with the ability to translate business requirements into scalable technical solutions.

Ability to lead technical discussions, mentor teams, and operate effectively in enterprise consulting environments.

Benefits

Opportunity to work on large-scale enterprise data modernization and cloud transformation initiatives.

Exposure to advanced technologies including Databricks, AI/ML, MLOps, and modern analytics platforms.

Collaborative environment with opportunities for technical leadership and professional growth.

Career development opportunities through continuous learning and certification support.

Opportunity to work with diverse customers and complex technology challenges.

Competitive compensation package.

Dynamic and innovative workplace focused on knowledge sharing and collaboration.

Inclusive culture that values diverse perspectives and contributions.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether? 

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