below marketmost similar roles pay hereabove market
This role pays less than
95%
of similar roles. Most pay
$149,500–$241,750
— the blue band above.
At the midpoint, this role pays about
$110k
versus about
$196k
for comparable roles.
Based on 240 similar postings.
Employer
About Cognizant
Cognizant is a multinational IT services and consulting company offering digital transformation, technology, and business process services. It serves clients across financial services, healthcare, manufacturing, and other industries worldwide.
Cognizant currently has
330 open roles
on FindRole.
Listed pay typically runs
$100,000–$135,000
across 211 roles with salary data.
The Databricks Genie AI Engineer/Semantic Layer Engineer joins the team to shape the data foundation powering natural language interactions and AI-enabled analytics. You will design and curate the semantic layer for Databricks Genie by defining table descriptions, synonyms, metric definitions, and business logic. Daily responsibilities include building and maintaining Genie Spaces, developing evaluation frameworks to test SQL generation quality, and creating regression test suites to ensure answer accuracy. You will analyze failure modes and iterate on schema improvements or prompt tuning. Required skills include proficiency in SQL, Python, and Scala, along with experience in semantic modeling using dbt, LookML, or Databricks Metric Views. You must understand LLMs, RAG architectures, and cloud platforms like AWS, Azure, or GCP to solve complex business intelligence problems.
Design and curate the semantic layer including table descriptions, synonyms, and metric definitions for Databricks Genie.
Build and maintain Genie Spaces by iterating on data room composition and instructions to improve response accuracy.
Define and maintain metric views and business logic to ensure natural language queries map to governed KPIs.
Develop evaluation frameworks to test SQL generation quality and response correctness against ground-truth business questions.
Build regression test suites to ensure data model changes do not degrade AI answer quality.
Analyze failure modes such as join errors or misinterpreted metrics and iterate on schema and prompt improvements.
Partner with DevOps to manage deployment, versioning, and monitoring of Genie Spaces and custom AI services.
Translate stakeholder feedback into concrete improvements for data models, prompts, and configurations.
What we're looking for
Experience working with Databricks, including Databricks SQL, Unity Catalog, and Genie or comparable AI-powered analytics capabilities.
Strong proficiency in SQL and programming languages such as Python and/or Scala.
Experience designing and managing semantic models, metric layers, or business-friendly data abstractions.
Knowledge of data warehousing, dimensional modeling, and analytics best practices.
Experience developing testing and validation frameworks for analytics, reporting, or AI-driven solutions.
Understanding of large language models (LLMs), generative AI applications, prompt engineering, retrieval-augmented generation (RAG), or related AI technologies.
Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).
Experience with semantic modeling or metric layers (dbt, LookML, or Databricks Metric Views) (preferred).