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Work setup in the employer’s posting: TELECOMMUTEFrom the employer’s posting
Design shared data and AI architecture on Databricks for Agentic AI solutions
Define data modeling standards for IoT and time-series domains
Architect ingestion and processing pipelines using Spark and Delta Lake
Establish governance, lineage and access controls with Unity Catalog
Design RAG retrieval patterns, indexing strategy and Vector Search datasets
Design shared data and AI architecture on Databricks across Agentic AI solutions
Define data modeling standards for IoT and time-series domains aligned to analytics and RAG needs
Architect ingestion and processing pipelines using Spark and Delta Lake
Establish governance, lineage and access controls with Unity Catalog
Design RAG retrieval patterns including indexing strategy and datasets for Vector Search
Databricks architecture experience in production environments
Data modeling expertise including event, time-series, dimensional and canonical modeling patterns
IoT and time-series data experience including scale, retention and query optimization
Delta Lake expertise including table design, performance tuning and lifecycle management
Databricks Unity Catalog experience covering governance, lineage and fine-grained access control
Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 2
Early. Similar jobs usually come down between day 7 and day 53.
From 7,804 similar postings that came down. Coming down is not always a hire.
656 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
We are seeking a Data and AI Architect to design shared data architecture for Agentic AI solutions on Databricks. You will shape secure ingestion, modeling and governance for IoT and time-series data and enable RAG retrieval patterns using Delta Lake, Unity Catalog, Spark and Vector Search. You simplify complexity and guide teams toward scalable, reusable designs. You will define the shared data architecture for Agentic AI solutions built on Databricks. Your focus is creating a secure, scalable and reusable foundation for ingestion, modeling, governance and retrieval patterns that enable AI-ready data products. You bring a pragmatic systems mindset, and you can translate complex data and AI requirements into clear architecture decisions. You collaborate across engineering, product and security teams, challenge assumptions constructively and manage risks early. Responsibilities Design shared data and AI architecture on Databricks across Agentic AI solutions Define data modeling standards for IoT and time-series domains aligned to analytics and RAG needs Architect ingestion and processing pipelines using Spark and Delta Lake Establish governance, lineage and access controls with Unity Catalog Define secure data access patterns for internal teams and downstream consumption Design RAG retrieval patterns including indexing strategy and datasets for Vector Search Produce architecture decision records, reference designs and reusable templates Partner with stakeholders to align scope, manage risks and drive implementation quality Requirements Databricks architecture experience in production environments Data modeling expertise including event, time-series, dimensional and canonical modeling patterns Ingestion pipeline experience across batch and streaming patterns IoT and time-series data experience including scale, retention and query optimization Delta Lake expertise including table design, performance tuning and lifecycle management Databricks Unity Catalog experience covering governance, lineage and fine-grained access control Apache Spark expertise for large-scale processing and optimization Data governance and security experience including policy design and secure-by-default architecture Nice to have Experience implementing Vector Search and managing embedding lifecycle Familiarity with retrieval quality, evaluation signals and RAG tuning considerations Experience enabling shared data products across multiple teams
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
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Australia
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