Databricks Architect
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Position Title : Databricks Architect
Experience : 12+ Years
Location : Noida/Gurugram/Pune/Bangalore(Hybrid)
Duration : 3 months contract(Will convert to Full time based on performance)
About the Role
We are looking for a Databricks Architect with deep Data Engineering expertise to build lakehouse solutions that are scalable, reliable, and secure. The architect will work closely with customers to design customised data platforms that accelerate analytics, reporting, and advanced use cases.
Key Role & Responsibilities
Define lakehouse architecture: medallion (bronze/silver/gold) patterns, batch/streaming designs, and multi-workspace strategies.
Design and implement data pipelines using Spark, Delta Lake, and Databricks workflows (Jobs/Workflows, DLT where applicable).
Establish governance and security using Unity Catalog, access controls, lineage, and data quality gates.
Optimise performance: cluster policies, autoscaling, partitioning, file sizing, caching, Spark tuning, and job orchestration.
Build CI/CD and release governance for notebooks, repos, jobs, and infrastructure-as-code.
Integrate Databricks with enterprise ecosystem (cloud storage, event streaming, data warehouse, BI tools).
Conduct solution workshops with customers; provide options and trade-offs; create phased implementation roadmaps aligned to business value.
Mentor teams, enforce engineering standards, and ensure operational excellence (monitoring, incident response, SRE practices).
Must Have
12+ years experience with a strong Data Engineering background (ETL/ELT, distributed compute, production-grade pipelines).
5+ years hands-on Databricks experience in architecture/technical leadership roles.
Strong experience in Apache Spark (PySpark/Scala), Delta Lake, pipeline design, and performance tuning.
At least 1 Databricks Certification.
Experience with data orchestration and DevOps practices (Git, CI/CD, testing frameworks).
Experience designing secure data platforms (RBAC, secrets, network/security integration, compliance considerations).
Strong customer-facing skills: requirements discovery, solution design, and stakeholder management.
Good to Have
Streaming experience (Kafka/Event Hubs, Structured Streaming, CDC patterns).
ML/AI enablement experience (MLflow, feature engineering, model lifecycle) as it relates to platform design.
Cloud certifications or platform-specific certifications.
Education
Bachelor’s/Master’s in Computer Science, Engineering, or related fields.
Key Skills: Databricks, Python, Spark, Data Architecture, Data Pipelines
Required
Preferred