Chief Lakehouse Architect – Databricks CoE

Jade Global; Hyderabad; On-site; INR 2,500,000 - 3,500,000; Full time

Job summary

Jade Global is looking for a Chief Lakehouse Architect in Hyderabad to define and execute enterprise-grade Databricks Lakehouse architecture standards. The role involves guiding complex solution designs and driving cost optimization across clients.

The ideal candidate will have substantial experience in data architecture and hands-on expertise with Databricks and Apache Spark.

Key responsibilities include defining reference architectures, leading migrations, and mentoring teams.

Qualifications

• 12–15 years in data architecture.
• 5–7 years hands-on Databricks & Apache Spark.
• 3+ years designing enterprise Databricks platforms.

Responsibilities

• Define Databricks reference architectures.
• Own standards for Delta Lake and medallion architecture.
• Design multi-workspace Databricks platform architectures.
• Lead Databricks migrations from legacy data warehouses.
• Design and approve architecture for all Databricks deals.

Skills

Databricks platform internals & optimization

Spark performance tuning and scalability

Delta Lake internals (ACID, compaction, Z-order)

Databricks Jobs, Workflows, CI/CD, IaC

Cloud-native Databricks (AWS / Azure / GCP)

Cluster tuning & auto-scaling strategies

Cloud billing & monitoring tools

Cost optimization patterns for Spark workloads

Job description

Chief Lakehouse Architect – Databricks CoE1

Principal architect responsible for defining and executing enterprise‑grade Databricks Lakehouse architecture standards, engagements and guiding complex solution designs. Drive cost optimization and financial governance for Databricks platforms across clients and internal workloads.

Key Responsibilities

• Define Databricks reference architectures (batch, streaming, ML, GenAI)
• Own standards for Delta Lake, medallion architecture, Unity Catalog
• Design multi‑workspace Databricks platform architectures
• Lead Databricks migrations from legacy data warehouses programs
• Design, review and approve architecture for all Databricks deals
• Mentor architects and senior Databricks engineers
• Define Databricks FinOps framework
• Optimize cluster policies, DBU usage, and job scheduling
• Work with engineering teams on performance‑to‑cost optimization
• Advise leadership and clients on Databricks cost strategies

Experience

• 12–15 years in data architecture
• 5–7 years hands‑on Databricks & Apache Spark
• 3+ years designing enterprise Databricks platforms, managing Databricks costs at scale

Skills

• Databricks platform internals & optimization
• Spark performance tuning and scalability
• Delta Lake internals (ACID, compaction, Z‑order)
• Databricks Jobs, Workflows, CI/CD, IaC
• Cloud‑native Databricks (AWS / Azure / GCP)
• Cluster tuning & auto‑scaling strategies, Databricks DBU model & pricing
• Cloud billing & monitoring tools
• Cost optimization patterns for Spark workloads

Certifications (Preferred)

• Databricks Data Engineer Professional
• FinOps Practitioner