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Databricks Lead
Service based company
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Databricks Lead

at Service based company

9 - 14 yrs
₹20L - ₹30L / yr
Chennai
Skills
databricks
Spark
Apache Spark
skill iconPython
ETL

Key Responsibilities


 Architect and implement enterprise-grade Lakehouse solutions using Databricks

 Design and deliver scalable batch and real-time data pipelines using Apache Spark (PySpark/SQL)

 Build ETL/ELT pipelines, incremental data loads, and metadata-driven ingestion frameworks

 Implement and optimize Databricks components: Delta Lake, Delta Live Tables, Autoloader, Structured Streaming, and Workflows

 Design large-scale data warehousing solutions with 3NF and dimensional modeling

 Establish data governance, security, and data quality frameworks, including Unity Catalog

 Lead ML lifecycle management using MLflow and drive AI use cases (RAG, AI/BI)

 Manage cloud-native deployments on Microsoft Azure and integrate with enterprise systems (e.g., ServiceNow)

 Drive CI/CD, DevOps practices, and performance optimization of Spark workloads

 Provide technical leadership, mentor teams, and ensure successful delivery

 Collaborate with stakeholders to translate business requirements into scalable solutions


Required Skills & Experience


 10+ years in Data Engineering / Analytics / AI with strong delivery ownership

 Deep expertise in Databricks ecosystem (Notebooks, Delta Lake, Workflows, AI/BI, Apps, Genie)

 Strong hands-on experience with: 

a. Apache Spark (performance tuning & scalability)

b. Python and SQL

 Proven experience in: 

a. Solution architecture and large-scale data platforms

b. Data warehousing and advanced data modeling

c. Batch and real-time processing systems

 Experience with: 

a. Azure Databricks and Azure data services

b. MLflow and MLOps practices

c. ServiceNow or enterprise integrations

 Exposure to AI technologies (RAG, LLM-based solutions)

 Strong stakeholder management and leadership skills


Certifications (Preferred)


 Databricks certifications aligned to data engineering and AI tracks, such as: 

a. Databricks Certified Data Engineer Associate (validates foundational ETL, Spark, and Lakehouse capabilities)

b. Databricks Certified Data Engineer Professional (advanced expertise in pipeline design, optimization, and governance)

 Certifications in Databricks Machine Learning or Generative AI tracks (e.g., ML Associate / Professional) for AI-driven use cases

 Relevant cloud certifications in Microsoft Azure or Amazon Web Services for platform deployment and architecture


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Shubham Vishwakarma

Full Stack Developer - Averlon
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