Job Title: Databricks Architect Location: Chennai/Bangalore/Hyderabad- Hybrid
Duration: Full time
Notice period: Immediate to 60 days max
Budget: Open to discuss
⚠️ Significant Note
Please do not apply if you have interviewed with Mastech Digital within the past 3 months. Duplicate/recent interview profiles may not be considered for this opportunity.
About the Role
We are looking for a seasoned Databricks Architect to lead the design, implementation, and governance of our enterprise-scale data platform for various customers. In this role, you will drive strategic decisions around our Lakehouse architecture, establish best practices for data engineering and ML workflows, and partner with cross-functional teams to deliver high-value, scalable data solutions.
You will serve as the technical authority on all things Databricks — from Delta Lake and Unity Catalog to MLflow and Databricks SQL — while mentoring engineers and aligning data initiatives with business objectives.
Key Responsibilities
Architecture & Platform Design
Design and own the end-to-end Databricks Lakehouse architecture, including Delta Lake, Unity Catalog, and multi-cloud deployments.
Establish reference architectures, design patterns, and standards for data ingestion, transformation, and serving layers.
Evaluate and integrate complementary technologies (e.g., Apache Kafka, dbt, Airflow) to build a robust modern data stack.
Lead capacity planning, cluster configuration, and infrastructure optimization to ensure performance and cost efficiency.
Data Engineering & Pipeline Development
Architect and oversee the development of scalable ELT/ETL pipelines using Spark, Delta Live Tables, and Databricks Workflows.
Define medallion architecture (Bronze/Silver/Gold)



standards and enforce data quality frameworks across all layers.
Drive adoption of streaming and batch processing patterns to support real-time and near-real-time use cases.
Governance & Security
Implement and manage Unity Catalog for fine-grained data access control, lineage tracking, and metadata management.
Establish data governance frameworks covering data classification, retention policies, RBAC, and compliance requirements.
Partner with security teams to ensure platform adherence to SOC 2, GDPR, HIPAA, or other relevant standards.
AI & ML Enablement
Design scalable feature engineering and ML training pipelines using MLflow and Databricks Feature Store.
Collaborate with data scientists to deploy and monitor ML models in production via Model Serving and Model Registry.
Champion AI tool adoption across the data team — curate approved tools, run enablement workshops, and track uplift metrics.
Develop internal AI coding assistants or Databricks notebook templates pre-loaded with team conventions, docstrings, and patterns.
Champion MLOps practices, including CI/CD for machine learning workflows and automated model retraining.
Leadership & Collaboration
Provide technical mentorship and hands-on guidance to a team of data engineers, analysts, and ML practitioners.
Act as a key stakeholder in data strategy discussions and translate business requirements into technical roadmaps.




Conduct architecture reviews, code reviews, and drive engineering excellence across the data platform.
Liaise with Databricks account teams to leverage new product capabilities and beta features.
Required Qualifications
8+ years of experience in data engineering, data architecture, or a closely related discipline.
5+ years of hands-on experience with Apache Spark, including performance tuning and optimization.
5+ years of production experience with Databricks, including cluster management, Delta Lake, and Databricks Workflows.
Deep expertise in cloud platforms – Azure (ADLS, Synapse), or GCP (BigQuery, GCS).
Strong proficiency in Python and PySpark for large-scale data processing.
Solid understanding of data modeling concepts — canonical modeling, dimensional modeling, Data Vault, and Lakehouse patterns.
Experience with Unity Catalog or equivalent metadata and governance frameworks.
Proven ability to design and deliver complex, cross-functional data enterprise solutions.
Excellent communication skills with the ability to present technical concepts to non-technical stakeholders.
Preferred Qualifications
Databricks Certified Data Engineer Associate or Qualified or Databricks Certified Associate Developer for Apache Spark certification.
Experience with real-time streaming technologies such as Apache Kafka, Kinesis, or Event Hubs.
Familiarity with AI agent frameworks and their integration with Databricks.
Exposure to Generative AI use cases, AI/ML lifecycle on Databricks
Background in Health Sciences, Financial Services or Retail domain.
Knowledge of Terraform or other infrastructure-as-code (IaC) tools for automated provisioning.

📌 Databricks Architect (Noida)
🏢 Mastech Digital
📍 Noida