Semantic & Genie Engineer - Databricks

Marktine Technology Solutions Pvt. Ltd.; United States; A distancia; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

Vriti is seeking a data engineering professional to advance governed semantic models and Genie-powered analytics across multi-domain questions. You will design SQL datasets, optimize queries, and build Databricks Metric Views with trusted patterns and scoring.

You will collaborate with business stakeholders and data product teams to deliver production-ready Genie experiences, ensure data quality, and iterate on routing/orchestration patterns for accurate, scalable answers.

Formación

• Experience with data discovery, profiling and data modeling.
• Hands-on with Databricks SQL, Unity Catalog, and Delta Lake.
• Experience designing governed semantic models and KPI definitions.
• Knowledge of Genie Agent configurations and semantic grounding.
• Familiarity with CI/CD, Git and engineering practices.

Responsabilidades

• Perform data discovery, profiling, source-to-business mapping, and analytical requirements translation.
• Design and optimize SQL datasets, dimensional/semantic models, views, and materialized views with clear grain and aggregation rules.
• Build and maintain governed Databricks Metric Views, including measures, dimensions, relationships, and business definitions.
• Configure and improve Genie Agents/Spaces with instructions, sample questions, trusted SQL patterns, and benchmark questions.
• Test answer accuracy, business semantics, performance, and consistency; diagnose fan-out, double counting, and incorrect responses.
• Implement and evaluate cross-domain Genie Agent routing/orchestration and integration patterns as required.
• Partner with business stakeholders, data product teams, and Solution Architecture to deliver reusable, production-ready solutions.

Conocimientos

SQL & data modeling

Advanced SQL techniques

Data profiling

Dimensional modeling

Databricks SQL & Unity Catalog

Databricks semantic layer

Genie Agent/Spaces

QA & validation

Cross-domain analytics

Performance tuning

Herramientas

Databricks

Delta Lake

Unity Catalog

Genie Agent/Spaces

Power BI

Tableau

Descripción del empleo

Key Responsibilities

• Perform data discovery, profiling, source-to-business mapping, and analytical requirements translation.
• Design and optimize SQL datasets, dimensional/semantic models, views, and materialized views with clear grain
• and aggregation rules.
• Build and maintain governed Databricks Metric Views, including measures, dimensions, relationships, and business
• definitions.
• Configure and improve Genie Agents/Spaces with instructions, sample questions, trusted SQL patterns, and
• benchmark questions.
• Test answer accuracy, business semantics, performance, and consistency; diagnose fan-out, double counting, and
• incorrect responses.
• Implement and evaluate cross-domain Genie Agent routing/orchestration and integration patterns as required.
• Partner with business stakeholders, data product teams, and Solution Architecture to deliver reusable, production-
• ready solutions.

Required Technical Skills

• SQL, Data Discovery & Modeling
• Advanced SQL: joins, CTEs, window functions, aggregation, deduplication, date logic, and query optimization.
• Data profiling: grain, cardinality, nulls, freshness, relationships, historical/SCD behavior, and data quality.
• Dimensional and semantic modeling: facts, dimensions, conformed dimensions, KPI definitions, aggregation
• correctness, and fan-out prevention.
• Databricks Semantic Layer
• Hands-on Databricks SQL, Unity Catalog, Delta Lake, views, and materialized views.
• Design and maintenance of Databricks Metric Views: measures, dimensions, joins/entities, and governed business
• definitions.
• Understanding of data access controls, lineage, performance, and semantic consistency across consumption
• tools.
• Genie & Conversational Analytics
• Hands-on Databricks Genie Agent/Space configuration, semantic grounding, instructions, and curated question
• patterns.
• Benchmark testing, SQL/answer validation, troubleshooting, and iterative tuning for trusted business responses.
• Ability to assess multi-agent routing and orchestration patterns for cross-domain analytical questions.

Engineering Practices

• Git-based development, testing, documentation, release discipline, and collaboration with engineering teams.
• Ability to explain complex analytical logic and results clearly to business and technical stakeholders.

Additional Skills (Nice to Have)

• dbt, Python, REST APIs, MCP integration, and Databricks Apps/Streamlit.
• the
• Experience implementing Genie One or custom supervisor-agent orchestration across multiple domains.
• Power BI/Tableau semantic models and enterprise-wide KPI alignment.
• Experience with reusable enablement frameworks, CI/CD automation, and Databricks cost optimization.

Ideal Contractor Profile

Hands-on engineer with 5+ years in data engineering, analytics, BI, or data platforms who can independently turn
unfamiliar business data into governed semantic models and accurate, production-ready Genie experiences. Combines
strong SQL and analytical judgment with business understanding, rigorous validation, and a reusable engineering
mindset.