Databricks Data Architect

Ascendum System Private Limited; Cincinnati (OH); Remote; USD 150,000 - 190,000; Full time

Job summary

Ascendum System Private Limited is seeking an experienced Data Architect to lead scalable Databricks solutions in Azure-centric cloud environments. You will own end-to-end architecture, mentor teams, and collaborate with stakeholders to drive modernization through data platforms.

The role combines hands-on design with strategic advisory, requiring strong Python/SQL, data modeling, and DevOps/IaC expertise. Some travel to Cincinnati may be required.

Qualifications

• Bachelor’s or master’s degree in CS, IT, or related field.
• 8+ years in data architecture, cloud data warehousing, or large-scale data integration.
• 3+ years delivering production-ready Databricks solutions.
• Strong Python, SQL, data modeling, and Azure services proficiency.

Responsibilities

• Architect scalable, high-performing data solutions meeting functional and non-functional requirements.
• Own the architecture, design, and optimization of Databricks platforms within Azure-focused ecosystems.
• Lead architecture workshops, requirements sessions, and whiteboard discussions with clients for scalable Databricks Lakehouse solutions.
• Define end-to-end data architectures with stakeholders and defend designs while guiding Databricks, Spark, Delta Lake, and cloud platforms.
• Lead hands-on implementation of data pipelines and infrastructure using DevOps and IaC practices.
• Partner with data engineering teams to ensure platform performance, reliability, and maintainability.
• Integrate Databricks solutions across systems following enterprise architecture standards.
• Create and review architecture documents for large-scale data initiatives.

Skills

Python

SQL

Data modeling

Azure services

Communication

Agile/Scrum

Education

Bachelor's or Master's in Computer Science / IT

Tools

Databricks

Azure Data Factory

Event Hub

Synapse

Terraform

ARM templates

CI/CD

Job description

Responsibilities

• Architect scalable, high-performing data solutions to meet both functional and non-functional requirements.
• Own the architecture, design, and optimization of Databricks platforms within cloud-based ecosystems (Azure preferred).
• Serve as the technical lead and trusted advisor for clients, facilitating architecture workshops, requirements discovery sessions, and whiteboard discussions to design scalable Databricks Lakehouse solutions that align with business objectives, data strategy, and modernization initiatives.
• Partner directly with business and technical stakeholders to define end-to-end data architectures, presenting and defending solution designs while providing hands‑on guidance for Databricks, Spark, Delta Lake, cloud platforms (Azure/AWS/GCP), data governance, and CI/CD best practices, roadmaps throughout the project lifecycle and lead whiteboarding sessions.
• Lead hands‑on implementation of data pipelines and infrastructure using best practices for DevOps and infrastructure‑as‑code.
• Partner with data engineering teams to ensure platform performance, reliability, and maintainability.
• Integrate Databricks solutions across systems, aligning with enterprise architecture standards and delivery best practices.
• Create and review architecture and solution design documents for large-scale data initiatives.
• Evangelize reuse and modular design through shared services and common data models.
• Enforce architectural standards and guide teams on patterns, tools, and delivery methods.
• Mentor and provide technical guidance to engineers during development and delivery.
• Contribute to risk management through proactive identification and mitigation of technical delivery risks.
• Operate at varying levels of abstraction—solutioning high-level architecture while diving deep when needed.

Required Qualification

• Bachelor’s or master’s degree in computer science, Information Technology, or related field.
• 8+ years of experience in data architecture, cloud data warehousing, or large-scale data integration.
• 3+ years of hands‑on experience delivering production‑ready Databricks solutions.
• Strong proficiency in Python, SQL, data modeling, and Azure services (Data Factory, Event Hub, Synapse, DevOps).
• Understanding of Databricks’ evolving AI offerings and practical experience designing agentic workflows, including RAG, API/tool integration, evaluation, and governance.
• Experience implementing infrastructure using Terraform, ARM templates, or similar IAC tools.
• Comfort working in Agile/Scrum environments and supporting CI/CD pipelines.
• Excellent communication skills—you can explain complex ideas to tech teams and business stakeholders alike.
• Bonus: Familiarity with ML lifecycle concepts and MLOps tools, even if you’re not a model builder yourself.

Other:

Remotely-working candidates can be considered, however, must be open to intermittent (3-5x/year) travel to Cincinnati, Ohio.