Data Architect

DataNimbus Inc.; India; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

DataNimbus Inc. is seeking a senior data platform architect to own the design and delivery of enterprise Databricks lakehouse solutions.

You will lead end‑to‑end migrations from legacy platforms, define architecture patterns, and mentor a cross‑functional team across analytics, engineering, and data science. The role involves building scalable pipelines with Delta Lake, Unity Catalog, and Structured Streaming, optimizing performance, cost, and security, and communicating decisions to

Qualifications

• 8+ years in data engineering or data platforms with production Databricks experience
• 2+ years as architect or technical lead owning platform design decisions
• Led end-to-end migrations to Databricks from legacy platforms at TB scale
• Led Databricks lakehouse implementations with medallion architecture and governance
• Production experience with Delta Lake, Unity Catalog, and Structured Streaming
• Advanced SQL and production-grade PySpark; Spark expertise applied to architecture decisions
• Deep cloud expertise (AWS, Azure or GCP) with Databricks and second cloud experience
• CI/CD and infrastructure-as-code for Databricks (Terraform, GitHub Actions, etc.)
• Consulting/customer-facing experience with strong communication

Responsibilities

• Own the design and delivery of enterprise Databricks lakehouse solutions.
• Lead end-to-end migrations from legacy platforms to Databricks at TB scale.
• Define architecture patterns, data modeling, and governance across projects.
• Mentor a cross-functional team and manage technical delivery for programs.
• Collaborate with customers and stakeholders to align on scope, risks, and timelines.

Job description

DataNimbus is an enterprise AI company with deep vertical solutions in financial services and industrial sectors. We build domain-native AI that understands how industries actually operate, not just how data flows through them. Our solutions are outcome-driven and industry-specific, delivering measurable results across how money moves, how assets perform, and how businesses grow. We go deep so our customers don't have to start from scratch.

With headquarters in the U.S. and offices in India and Canada, DataNimbus operates globally, fostering a culture of responsible innovation, adaptability, and customer-centricity. We pride ourselves on being a trusted partner for customers navigating the complexities of Data+AI and payment modernization.

What would help make your case:

• 8+ years in data engineering or data platforms, including 4+ years hands-on with Databricks in production.
• 2+ years as architect or technical lead, owning design decisions for a platform or program.
• Led at least 2 end-to-end migrations to Databricks from legacy platforms (e.g. Hadoop, Teradata, Oracle, Informatica, Synapse, Snowflake), each at TB scale or above.
• Led the design and delivery of at least 2 end-to-end Databricks lakehouse implementations, covering medallion architecture, data modeling (dimensional, Data Vault or similar), batch and streaming, Unity Catalog governance, and non-functional requirements (performance SLAs, cost, security, DR).
• Owned technical delivery of at least 1 Databricks program (team of 4+, 6+ months): scope, estimates, technical risks and timelines.
• Authored architecture artifacts used by delivery teams and customers: design documents, architecture decision records (ADRs), reference architectures and C4/solution diagrams. Redacted samples may be requested.
• Production experience with Delta Lake, Unity Catalog, Lakeflow/Delta Live Tables or Workflows, and Structured Streaming.
• Advanced SQL and production-grade PySpark (testing, packaging, code review), Scala a plus.
• Deep Apache Spark expertise (execution model, shuffle, Catalyst/Tungsten, memory, AQE, Structured Streaming state) applied to architecture decisions: data layout, partitioning and clustering strategy, cluster sizing and workload isolation.
• Deep expertise in one cloud (AWS, Azure or GCP) as it applies to Databricks (networking, IAM, storage, security), plus hands-on project experience in a second.
• Implemented CI/CD and infrastructure as code for Databricks in production (Databricks Asset Bundles, Terraform, GitHub Actions or Azure DevOps).
• Consulting / customer-facing experience, working with external clients across a variety of industry markets, including managing conflicting priorities and difficult stakeholder situations.
• Strong communication and collaboration skills.
• Excellent problem-solving skills.

Nice to have

MLOps / GenAI on Databricks: MLflow experiment tracking and model registry in Unity Catalog, feature tables, Model Serving, Lakehouse Monitoring for drift and data quality, and Vector Search for RAG. Includes designing the data pipelines that feed model training and inference

Why Join DataNimbus?

At DataNimbus, we believe in shaping a sustainable, AI-driven future while offering an environment that prioritizes learning, innovation, and growth.

Our core values- Customer-Centricity, Simplicity, Curiosity, Responsibility, and Adaptability- are the foundation of our workplace, ensuring every team member can make a meaningful impact. Joining DataNimbus means being part of a dynamic team where you can:

• Work with cutting-edge technologies and revolutionize workfl ows in Data+AI solutions.
• Contribute to solutions that are trusted by global businesses for their scalability, security, and efficiency.
• Grow personally and professionally in a culture that values curiosity and continuous learning. If you are passionate about innovation, ready to solve complex challenges with simplicity, and eager to make a difference, DataNimbus is the place for you.