Databricks Solution Architect

Location: Bengaluru, Karnataka, India | Experience: Senior (10–14 years)

About the Company

Diggibyte is hiring a Databricks Solution Architect to help shape modern data and analytics solutions for clients that want to move faster with cloud-native platforms. The role sits within Engineering and will support the design of scalable, secure, and production-ready data architectures that turn business requirements into reliable outcomes. The ideal candidate will bring strong Databricks expertise along with a practical understanding of cloud data platforms, integration patterns, and enterprise delivery. You will work closely with technical and business stakeholders to define the right architecture, guide implementation decisions, and ensure the solution performs well as usage grows. This is a hands-on architecture role for someone who can balance strategy with execution, simplify complexity, and help teams deliver measurable value through better data foundations.

About the Role

This role owns the technical design and solutioning for Databricks-based data platforms from discovery through delivery. You will translate client goals into clear architecture choices, define implementation standards, and ensure teams build solutions that are scalable, maintainable, and aligned to business needs. The position requires strong ownership of data platform design, stakeholder communication, and delivery quality. You will also help shape best practices across lakehouse architecture, data engineering, governance, and performance optimization. Success in this role means reducing delivery risk, improving platform reliability, and enabling teams to move from ideas to production with confidence.

Key Responsibilities

• Own Databricks solution architecture across data ingestion, transformation, storage, and serving layers so client requirements are translated into stable, scalable platform designs.
• Lead discovery sessions with business and technical stakeholders to clarify goals, constraints, dependencies, and success measures before solution design begins.
• Define target architectures, implementation standards, and design decisions that improve delivery quality, reduce rework, and keep the platform aligned with enterprise needs.
• Guide data engineering teams on lakehouse patterns, workspace design, security controls, performance tuning, and deployment practices that support production readiness.
• Review end-to-end solution builds to identify risks early, resolve architecture gaps, and ensure the final implementation meets functional and non-functional expectations.
• Partner with delivery, cloud, and analytics teams to align architecture with timelines, integration needs, and operational readiness so solutions launch cleanly and scale safely.
• Support client conversations on platform choices, trade-offs, and roadmap decisions so technical recommendations are easy to understand and tied to business impact.

Essential Skills & Technologies

• Deep hands-on experience with Databricks and modern data platform design, including lakehouse concepts, Spark-based processing, and scalable analytics workflows.
• Strong knowledge of cloud data architecture, integration patterns, governance, and security controls needed to build reliable enterprise-grade solutions.
• Practical experience with SQL, Python, and data engineering tooling so architecture decisions can be validated against real implementation constraints.
• Ability to design for performance, reliability, and cost awareness across ingestion, transformation, orchestration, and serving layers.
• Strong stakeholder management and communication skills, with the ability to simplify technical trade-offs for both business and engineering audiences.
• Experience reviewing solution designs, identifying risks, and guiding teams toward production-ready outcomes without losing delivery speed.
• Comfortable working in hybrid delivery environments where architecture, execution, and client collaboration all need to stay closely aligned.

Additional Plus

• Databricks certifications or equivalent cloud data platform credentials are a strong advantage.
• Experience leading enterprise migrations to Databricks or lakehouse-based analytics platforms will be especially valuable.
• Exposure to MLOps, data governance, or large-scale modernization programs will help the candidate add broader platform value.

What You'll Bring

• You bring strong architecture judgment and can turn vague business needs into clear platform decisions that teams can build with confidence.
• You bring practical Databricks experience and know how to balance speed, scalability, security, and maintainability in real delivery environments.
• You communicate well with stakeholders, keep technical discussions grounded in outcomes, and help teams move through complexity with clarity.
• You take ownership of quality and delivery risk, and you know how to prevent avoidable issues before they affect production.