Databricks Architect

NAVA Software Solutions; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

NAVA Software Solutions is seeking a Sr Data Architect to lead the design and governance of enterprise data platforms centered on Databricks in an AWS environment. The role requires setting technical direction, owning architecture decisions, and guiding data modernization initiatives across teams.

You will mentor engineers, define patterns like Medallion, Lakehouse, and Data Mesh, and drive production-grade data pipelines with Delta Live Tables, Unity Catalog, and MLflow integration.

Qualifications

• 10+ years data engineering/architecture experience (architecting solutions, not just executing tickets).
• 3+ years of substantial, hands-on Databricks experience in a Databricks-first environment.
• 5+ years hands-on with AWS cloud data services in production environments.

Skills

Databricks

AWS

SQL

Python

Data governance

Education

Bachelor's or Master's in CS/Engineering

Tools

Unity Catalog

Delta Lake

Databricks Workflows

MLflow

Job description

Title: Sr Databricks Architect

Location: Houston, TX (Onsite) Need Locals

Duration: 12+ Months

Tax Term: W2

The Sr. Data Engineer is a senior, hands-on technical leader responsible for architecting, building, and governing enterprise-wide data platforms in a Databricks-centric environment. This role goes beyond pipeline development ? the successful candidate will set technical direction, make build-vs-buy and platform design decisions, and be a trusted advisor to both engineering teams and business stakeholders. Deep, current expertise in Databricks (Unity Catalog, Delta Lake, workflow orchestration) and AWS is required, along with a track record of leading ? not just supporting ? large-scale data modernization initiatives. This is not a mid-level execution role; the client requires someone who can own architecture decisions with minimal oversight.

Job Description

Required Skills & Qualifications

• Bachelor?s or master?s degree in computer science, Engineering, or related field.
• 10+ years of data engineering/architecture experience, including at least 5 years in a senior or lead capacity (architecting solutions, not just executing tickets).
• 5+ years hands-on with AWS cloud data services in production environments.
• 3+ years of substantial, hands-on Databricks experience is required ? this client runs a Databricks-first environment. Candidates without recent Databricks depth will not be considered.
• Proficiency in AWS services: Glue, Redshift, Athena, Lake Formation, SageMaker, Bedrock, Step Functions.
• Deep Databricks expertise: Unity Catalog, Delta Lake, Delta Live Tables, Databricks Workflows, cluster/cost management, and MLflow.
• Working knowledge of the Alation data governance tool.
• Strong skills in SQL (T-SQL), Python (PySpark/Pandas), DAX, Power Query (M), PL/SQL.
• Experience with databases: SQL Server, Oracle, PostgreSQL, Azure SQL, Teradata.
• Skilled in Power BI, Git, Visual Studio Code, SSMS.
• Demonstrated command of architectural patterns: Medallion architecture, Data Mesh, Lakehouse, SOA data layers ? able to defend design trade-offs to senior stakeholders.
• AWS and Databricks certifications required or in progress (e.g., Databricks Certified Data Engineer Professional, AWS Certified Data Analytics/Solutions Architect).
• Prior experience owning data security, access control, and compliance posture in a regulated or enterprise environment.
• Excellent executive-level communication, collaboration, and technical leadership abilities ? comfortable presenting architecture decisions to non-technical stakeholders.
• Own and evolve the enterprise data architecture roadmap, ensuring alignment with business strategy and long-term scalability.
• Architect and lead implementation of scalable data systems, including Data Lakes, Lakehouse, and Data Mesh patterns, with Databricks as the core platform.
• Design and enforce Medallion architecture (bronze/silver/gold) standards across ingestion, transformation, and consumption layers.
• Lead cloud migration strategies and end-to-end data modernization projects, including legacy platform decommissioning.
• Architect, optimize, and troubleshoot batch and streaming pipelines using AWS Glue, Databricks Workflows, and Delta Live Tables.
• Manage Databricks workspace administration: cluster sizing/cost optimization, Unity Catalog access controls, and job orchestration.
• Implement enterprise data governance, metadata management, lineage tracking, and compliance frameworks (Alation).
• Integrate data platforms to support AI/ML workflows (SageMaker, Bedrock, Databricks MLflow) and enable production-grade model deployment.
• Establish and enforce engineering standards for CI/CD, version control, testing, and documentation across the data engineering team.
• Serve as technical lead and mentor for data analysts and engineers, including code/design review and career development.
• Lead technical assessments, architecture review boards, and stakeholder workshops; translate business requirements into technical design.
• Own production support escalations for critical data pipelines and drive root-cause analysis and remediation.
• Evaluate emerging tools and platform capabilities, and make recommendations that materially affect the client's data strategy.

Preferred Experience

• Prior experience as a data architect or technical lead of record on a Databricks migration or greenfield build.
• Designing and implementing scalable data architectures spanning both AWS and Databricks.
• Managing data governance, security, and compliance in complex, multi-source enterprise environments.
• Formally mentoring or managing junior/mid-level architects and engineers.
• Experience in energy, midstream, or industrial sectors.
• Working with cross-functional teams to deliver measurable business value through data.

Additional Information

• This role may require occasional travel for stakeholder workshops or technical assessments.
• The Sr. Data Engineer will play a key role in shaping the organization's data strategy and future readiness for AI/ML initiatives, and is expected to operate with senior-level autonomy from day one.