
Role & Responsibilities
- Lead enterprise-scale implementation of data warehouse data platforms on Databricks and Snowflake environments.
- Design and implement Medallion (Bronze/Silver/Gold) architecture and scalable enterprise data models.
- Establish data modeling standards (dimensional, data vault, lakehouse patterns) and ensure best practices across projects
- Establish enterprise data governance frameworks including cataloging, lineage, stewardship, and compliance using Atlan.
- Define and implement CI/CD pipelines for infrastructure and data platform deployments
- Design data architectures that support AI/ML and Generative AI workloads including vector storage, feature layers, and secure access patterns.
- Build scalable ingestion frameworks supporting batch, streaming, and CDC pipelines.
- Architect secure, high-performance data integration layers for analytics, BI, and AI consumption.
- Develop target-state architecture blueprints and enforce data standards, governance, and best practices across teams.
- Collaborate with engineering, analytics, and data science teams to ensure platform alignment and scalability.
- Engage with clients as a trusted advisor, driving data strategy, roadmap definition, and identifying opportunities for expansion.
Ideal Candidate
- Strong Databricks / AWS Data Architect profile
- Mandatory (Experience 1) – Must have minimum 8+ years of experience in Data Architecture / Data Engineering, with exposure in enterprise-scale data platform modernization initiatives
- Mandatory (Experience 2) – Must have minimum 3+ years of deep hands-on experience in Databricks-based lakehouse architecture on AWS, including large-scale data platform implementations
- Mandatory (Experience 3) – Strong expertise in Databricks ecosystem including Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, and MLflow with focus on performance optimization and security
- Mandatory (Experience 4) – Strong experience with AWS data services including S3, Glue, EMR, Lambda, Redshift, Athena, Lake Formation, and DMS, with strong understanding of cloud-native architecture patterns
- Mandatory (Experience 5) – Proven experience designing and implementing Medallion (Bronze/Silver/Gold) architecture, scalable data models (Dimensional/Data Vault), and enterprise lakehouse platforms supporting batch and real-time processing
- Mandatory (Experience 6) – Must have hands-on experience building scalable ingestion frameworks including batch, streaming, and CDC pipelines using tools like Kafka, Kinesis, Spark, or similar technologies
- Mandatory (Skill 1) – Proven experience implementing CI/CD pipelines for data platforms, including infrastructure as code, automated deployments, and environment management
- Mandatory (Skill 2) – Hands-on experience enabling data platforms for AI/ML and Generative AI use cases, including feature stores, vector storage, and secure data access patterns
- Mandatory (Skill 3) – Experience with orchestration tools such as Apache Airflow or MWAA and designing integration layers for analytics, BI, and AI consumption
- Preferred (Company) – Product Companies.
- Preferred (Certification) – AWS / Databricks / Snowflake certifications; experience with Snowflake alongside Databricks; exposure to MDM, data quality frameworks, and enterprise metadata tools

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Professor:
To drive the campus academic operations in close coordination with,
a) Head of Departments. b) Faculty members c) Students
To create an 'IT centre of excellence' at the campus.
Should have driven the academic function of IT dept.
Should have experience of handling the academic operations
Associate / Assistant Professor:
Adhering to university time line (other the new courses)
To ensure coverage of Syllabus as per university standards
Learning Outcome
Examination Result ( Includes both Internal & Main Exams)
Knowledge Improvement Program
Innovation & Development
Technical Skills:
- General: C++, Java, OS, RDBMS, Software Engg, Data Structure etc
- Niche technologies like Cloud, Mobility, Information security, Data Science, IoT and Artificial Intelligence to name a few
Behavioural Competencies:
- Strong Leadership Qualities
- Excellent Communication skills
- Strong interpersonal skills to work with diverse teams
- Strong Presentation Skills
Qualification: B.Tech, M.Tech & Ph.D - Completed / Pursuing
Year of Exp:
- Professor: Min 12+ years of exp post PG and 5 years post Ph.D
- Associate Professor: Min 10+ years of exp post PG and 3 years post Ph.D
- Assistant Professor: 2+ years exp
How you match
Skills
-
MatchTeaching
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No matchData Privacy
-
No matchInternet of Things (IoT)
-
No matchArtificial Intelligence (AI)
-
No matchCurriculum
-
No matchNetwork Security
-
No matchPresentation Skills
-
No matchInformation Security
-
No matchRDBMS
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No matchInterpersonal Skills.











