DataBricks Architect

Cognizant; United States; On-site; USD 150,000 - 230,000; Full time

Job summary

Cognizant is seeking a senior Databricks Architect to act as the embedded technical POC, designing Lakehouse architectures and governing platforms across ingestion, transformation, and security. The role requires hands-on expertise with Delta Lake, Unity Catalog, and Spark, plus leadership in client workshops and solutioning for expansion opportunities.

Responsibilities include guiding GenAI integration, supervising governance, and communicating escalations to executive stakeholders.

Qualifications

• 12+ years IT/tech experience including data engineering/architecture.
• 3-5+ years hands-on Databricks experience with pipelines and platform config.
• Senior/Principal Architect level judgment with hands-on Lead Engineer capability.
• Hands-on expertise in Unity Catalog, Delta Lake, Spark, Workflows, and security.
• Active Databricks certification required (e.g., Data Engineer Pro or Architect).
• Proficiency with GenAI frameworks and their Databricks integration.
• Experience with Kubernetes/container deployments in data/AI contexts.
• Strong client-facing stakeholder management and executive communication.

Responsibilities

• Serve as the embedded Databricks architect and primary technical POC for the account.
• Design, review, and contribute to Lakehouse architecture across ingestion, transformation, and governance layers.
• Own solution design for Unity Catalog, Delta Lake, Spark, Workflows, and security.
• Provide hands-on engineering support—code reviews, pipeline troubleshooting, performance tuning, cost optimization.
• Guide adoption of GenAI capabilities with Databricks where relevant to use cases.
• Translate data/AI use cases into Databricks-native solutions with client stakeholders.
• Define and enforce platform governance standards across the Databricks estate.
• Own end-to-end escalation management and executive communications.

Skills

Databricks architecture

Senior architect

Kubernetes

GenAI frameworks

Client-facing communication

Cloud data engineering

Education

Databricks certification

Tools

Databricks

Spark

GenAI integration

Job description

*** NO VISA DEPENDENT candidates will be considered for this role***

MUST have 18+ years of total experience

• Serve as the embedded, hands-on Databricks architect and acting as the primary technical point of contact for the account.
• Design, review, and directly contribute to Lakehouse architecture spanning ingestion, transformation, orchestration, governance, and consumption layers.
• Own solution design for core Databricks capabilities including Unity Catalog, Delta Lake, Spark Declarative Pipelines, Workflows, cluster and compute strategy, and platform security.
• Provide hands-on engineering support - code reviews, pipeline troubleshooting, performance tuning, and cost optimization - working directly with client and delivery engineering teams.
• Guide adoption of emerging Databricks capabilities (e.g., Genie/Genie Ontology, Lakebase, Databricks Dashboards, Agent Bricks, Model Serving, DABs) where relevant to the use cases.
• Partner with client's business and IT stakeholders to translate data and AI use cases into Databricks-native solutions.
• Define and enforce platform governance standards - data access, security, cost management, environment provisioning, and change control - across the Databricks estate.
• Own technical escalation management end-to-end: triage, root-cause analysis, remediation, and executive-ready communication for critical issues.
• Run governance forums/steering checkpoints with client stakeholders and internal delivery leadership; track and report platform health, risks, and open items.
• Act as the technical bridge between the customer, Cognizant delivery teams, and Databricks account/field teams on architecture decisions and platform roadmap.
• Support RFP/proposal responses and technical solutioning for expansion opportunities.
• Lead or co-lead client workshops (discovery, architecture design sessions, roadmap planning) to identify new Databricks use cases and revenue opportunities.
• Contribute to the build-out of reusable Databricks accelerators/offerings in partnership with the FDE CoE (e.g., migration accelerators, industry solution patterns).
• Represent Cognizant's Databricks capability in client-facing forums, bringing forward account-specific recommendations back to the FDE CoE leadership.

Required Qualifications

• 12+ years of overall IT/technology experience, including significant time in data engineering and/or architecture roles.
• 3-5+ years of hands-on Databricks experience - able to build, debug, and optimize pipelines and platform configuration directly, not just review at a design level.
• Operates at a Senior/Principal Architect level of judgment and communication, while remaining comfortable working hands-on at a Lead Engineer level when needed.
• Mandatory hands-on/architecture-level expertise in core Databricks capabilities:
• Unity Catalog (governance, access control, lineage)
• Delta Lake / Spark Declarative Pipeline (Lakehouse Federation optional)
• Apache Spark (batch and structured streaming)
• Workflows/Jobs orchestration and cluster/compute management
• Platform security, networking, and cost governance
• At least one current, active Databricks certification is mandatory (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Associate/Professional Solutions Architect).
• Working proficiency with GenAI/agentic AI frameworks (LLM-based pipelines, RAG, agent orchestration) and their integration with Databricks (e.g., Mosaic AI, Model Serving).
• Hands-on experience with Kubernetes/containerized deployments in a data or AI platform context.
• Demonstrated experience in client-facing stakeholder management, escalation handling, and executive-level communication.