7 часов назад
Data Architect - Databricks (GenAI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Architect - Databricks (GenAI) (Databricks, Snowflake, AWS): Architecting scalable enterprise data platforms using Medallion architecture, governed data models, and batch and real-time processing with an accent on data governance, CI/CD, and AI/ML-ready foundations. Focus on designing secure cloud-native ecosystems, building ingestion and streaming frameworks, and aligning architecture standards across engineering, analytics, and data science teams.
Location: Mumbai, Bengaluru, Hyderabad, or Gurgaon, India; hybrid work with three days per week in the office
Company
is delivering an enterprise data modernization initiative focused on cloud-native data platforms and AI-ready foundations.
What you will do
- Lead enterprise data platform implementations across Databricks and Snowflake environments.
- Design Medallion architecture, scalable enterprise data models, and target-state architecture blueprints.
- Establish governance frameworks covering cataloging, lineage, stewardship, compliance, and metadata management using Atlan.
- Build batch, streaming, real-time, and CDC ingestion frameworks and secure data integration layers.
- Enable AI/ML and Generative AI workloads through vector storage, feature layers, and secure access patterns.
- Collaborate with engineering, analytics, and data science teams while advising clients on data strategy and roadmaps.
Requirements
- At least 10 years of experience in data and analytics architecture, including large-scale enterprise modernization initiatives.
- Advanced Databricks expertise, including Delta Lake, Databricks SQL, Unity Catalog, Delta Live Tables, MLflow, optimization, and security.
- Strong experience with the AWS data ecosystem, including S3, Glue, EMR, Lambda, Redshift, Lake Formation, Athena, and DMS.
- Experience with data warehousing, dimensional and Data Vault modeling, MDM, data quality, metadata management, and data catalogs.
- Experience with Kafka, Kinesis, or similar streaming technologies, plus orchestration tools such as Apache Airflow or MWAA.
- Ability to join immediately or within two weeks is prioritized.
Nice to have
- AWS, Databricks, or Snowflake certifications.
Culture & Benefits
- Hybrid working arrangement with three office days per week.
- Cross-functional collaboration across engineering, analytics, and data science.
- Opportunity to shape enterprise architecture standards, governance, and data modernization strategy.
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