Job Title: Semantic & Genie Engineer – Databricks
Experience: 5+ Years
Platform: OneData / Databricks
Job Summary
We are looking for an experienced Semantic & Genie Engineer to build trusted, business-ready semantic assets and conversational analytics experiences on the OneData platform powered by Databricks.
The ideal candidate will have strong SQL skills, hands-on experience with Databricks Metric Views and Genie Agents/Spaces, and a solid understanding of analytical modeling, business metrics, and data governance.
The role involves translating business requirements into governed semantic models, configuring and validating Genie experiences, and ensuring analytical responses are accurate, consistent, performant, and ready for production.
Key Responsibilities
- Perform data discovery, profiling, source-to-business mapping, and analytical requirements analysis.
- Translate business requirements into SQL datasets, dimensional models, semantic models, views, and materialized views.
- Define data grain, relationships, aggregation rules, and business metrics to ensure analytical accuracy.
- Build and maintain governed Databricks Metric Views, including measures, dimensions, relationships, and business definitions.
- Configure and enhance Databricks Genie Agents/Spaces using clear instructions, curated sample questions, trusted SQL patterns, and benchmark questions.
- Validate Genie responses for SQL correctness, business semantics, consistency, and performance.
- Diagnose issues such as fan-out, double counting, incorrect aggregations, and inaccurate analytical responses.
- Perform iterative testing and tuning to improve the reliability of conversational analytics.
- Evaluate cross-domain Genie Agent routing, orchestration, and integration patterns for complex analytical questions.
- Maintain semantic consistency, data lineage, and appropriate access controls across analytical consumption tools.
- Collaborate with business stakeholders, data product teams, and Solution Architecture to deliver reusable, production-ready solutions.
- Follow Git-based development, testing, documentation, and release management practices.
- Explain analytical logic, business metrics, and technical findings clearly to both business and technical stakeholders.
Required Technical SkillsSQL, Data Discovery & Modeling
- Advanced SQL skills, including joins, CTEs, window functions, aggregations, deduplication, date logic, and query optimization.
- Experience in data profiling, including grain, cardinality, null values, freshness, relationships, historical data, and Slowly Changing Dimensions (SCD).
- Strong understanding of dimensional and semantic modeling, including facts, dimensions, and conformed dimensions.
- Ability to define KPIs, establish correct aggregation rules, and prevent fan-out and double-counting issues.
- Experience translating business requirements into analytical datasets and reusable data models.
Databricks Semantic Layer
- Hands-on experience with Databricks SQL, Unity Catalog, Delta Lake, views, and materialized views.
- Experience designing and maintaining Databricks Metric Views, including measures, dimensions, joins/entities, and governed business definitions.
- Understanding of data access controls, data lineage, performance optimization, and semantic consistency across consumption tools.
- Ability to build reliable semantic assets that support consistent business reporting and analytics.
Genie & Conversational Analytics
- Hands-on experience configuring Databricks Genie Agents/Spaces.
- Knowledge of semantic grounding, Genie instructions, curated question patterns, and trusted SQL generation.
- Experience with benchmark testing, SQL and answer validation, troubleshooting, and iterative tuning.
- Ability to evaluate the accuracy and reliability of conversational analytics responses.
- Understanding of multi-agent routing and orchestration patterns for cross-domain analytical questions.
Engineering Practices
- Experience with Git-based development, testing, technical documentation, and release management.
- Ability to collaborate with data engineering and architecture teams.
- Strong analytical judgment and communication skills.
- Focus on maintainability, reusability, data quality, and production readiness.
Nice-to-Have Skills
- Experience with dbt, Python, REST APIs, or MCP integrations.
- Familiarity with Databricks Apps and Streamlit.
- Experience with Genie One or custom supervisor-agent orchestration across multiple domains.
- Knowledge of Power BI or Tableau semantic models and enterprise KPI alignment.
- Experience building reusable enablement frameworks and CI/CD automation.
- Familiarity with Databricks cost optimization and performance tuning.
Ideal Candidate Profile
We are looking for a hands-on engineer with 5+ years of experience in data engineering, analytics, business intelligence, or data platforms.
The ideal candidate can independently understand unfamiliar business data, translate requirements into governed semantic models, and deliver accurate, production-ready Databricks Genie experiences. Strong SQL expertise, business understanding, rigorous validation, and a reusable engineering mindset are essential.
How to Apply
Interested candidates can share their updated resume at hr@spasnik.com or reach out via direct message.
Pay: ₹1,500,000.00 - ₹2,500,000.00 per year
Work Location: Hybrid remote in Hyderabad, Telangana
