Responsibilities

- Lead enterprise pre-sales engagements, including discovery workshops, solution architecture design, technical proposals, and executive presentations to CTOs, CDOs, and engineering leadership
- Design and define modern Lakehouse architectures on Databricks, leveraging Delta Lake, Delta Live Tables, Unity Catalog, Databricks SQL, MLflow, and related platform capabilities
- Own the technical direction of delivery engagements and lead a team of 4–8 data engineers by conducting design reviews, code reviews, and enforcing quality standards
- Collaborate with account managers and practice leaders to qualify opportunities, estimate effort, define delivery approaches, and support commercial proposals
- Assess customer data platforms, identify capability gaps, and develop migration or modernization roadmaps
- Establish governance, security, and compliance frameworks, including data lineage, auditability, access controls, and data quality practices
- Develop reusable accelerators, reference architectures, delivery frameworks, and best practices to improve delivery efficiency and consistency
- Represent the organization as a Databricks and Lakehouse subject matter expert at customer engagements, partner forums, industry events, and technical communities
- Mentor and coach data engineers and architects, contributing to capability development across the practice

Requirements

- 10+ years of hands-on experience in data engineering and data platform development
- 5+ years of production experience with Databricks, including Unity Catalog,



Delta Lake, Spark Structured Streaming, Databricks Workflows, and Databricks SQL
- Proven experience designing and delivering enterprise-scale Lakehouse solutions supporting large-scale data environments and governance requirements
- Solid programming skills in Python and/or Scala for Spark-based workloads, with advanced SQL proficiency
- Experience working directly with enterprise customers in consulting, professional services, or system integration environments
- Demonstrated ability to lead workshops, create Statements of Work (SOWs), define solution architectures, and engage senior business and technology stakeholders
- Deep understanding of data governance, security, lineage, auditability, and regulatory compliance within modern data platforms
- Databricks Certified Data Engineer Professional and/or Databricks Certified Associate Developer for Apache Spark certification
- Experience implementing Databricks across AWS, Azure, and GCP environments
- Familiarity with the broader data ecosystem, including dbt, Fivetran, Tableau, Power BI, and related technologies
- Experience with Databricks Feature Store, MLflow, and ML-integrated data engineering workflows
- Prior experience in a Senior Architect, Principal Architect, or similar leadership role within a consulting organization, systems integrator, or Databricks partner
- Contributions to the data engineering community through technical blogs, conference presentations, open-source projects, or thought leadership content

📌 Associate Architect / Architect - Databricks (Thiruvananthapuram)
🏢 QBurst
📍 Thiruvananthapuram