Senior Databricks Engineer, Analytics

Manning Global AG

. Work with reporting owners to document KPI definitions, calculation rules, source mappings, dimensions, filters and acceptance criteria .

Posted 10/23/2026full-timeRemote • IndiaSenior💰 ₹1,500,000 - ₹1,800,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in BI and analytics engineering with a strong focus on SQL, Power BI, and DAX for data validation and semantic modeling. Capable of translating business requirements into testable criteria and conducting thorough user acceptance testing.

Highest-signal resume keywords

Advanced SQLPower BI/DAX SkillsData ValidationSemantic ModelingUser Acceptance Testing

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Semantic ModelingData ValidationSQLDAXDimensional ModelingData ReconciliationTesting ProceduresData Quality AutomationMetric ViewsAcceptance Criteria

Soft Skills

Attention to DetailCommunicationStakeholder Engagement

Tools & Technologies

Power BIDatabricks SQLPythonMicrosoft Fabric LakehouseUnity Catalog

Industry Keywords

Telecom ReportingSubscription ReportingSales ReportingNetwork Reporting

Tech Stack

Tools & technologies

PythonSQLUnity

About the role

Key responsibilities & impact

Work with reporting owners to document KPI definitions, calculation rules, source mappings, dimensions, filters and acceptance criteria
Analyse Power BI semantic models and DAX measures to understand authoritative reporting logic
Develop reference SQL and test datasets; work with the Databricks engineer to translate approved logic into metric views and supporting queries
Reconcile results across source data, reporting models and Genie answers, documenting and resolving discrepancies with the appropriate owner
Test aggregation, distinct counts, ratios, date boundaries, missing values, duplicate records and differences in data refresh timing
Create a benchmark question set with approved reference answers, tolerances and repeatable regression checks
Assess answer relevance, table/chart consistency, document citations and behaviour when questions are ambiguous or unsupported
Test that users receive only the results permitted by the agreed access model
Coordinate user acceptance testing, track defects and prepare evidence for business sign-off
Document KPI definitions, validation procedures and known limitations for handover

Requirements

What you’ll need

Strong BI or analytics engineering experience; typically 4+ years with hands-on semantic modelling and data validation
Advanced SQL and strong Power BI/DAX skills, including relationships, filter context, time intelligence and measure behaviour
Experience reconciling numbers across reports or systems and tracing discrepancies to data, business definitions or calculation logic
Understanding of dimensional modelling, fact-table grain, joins and additive/non-additive measures
Ability to build repeatable data checks using SQL and a scripting or testing tool, such as Python
Experience turning business requirements into testable acceptance criteria and supporting UAT
English communication, strong attention to detail and confidence discussing KPI definitions with business stakeholders
Preferred: Databricks SQL, Unity Catalog and metric views
Preferred: Databricks Genie or other conversational analytics evaluation
Preferred: Microsoft Fabric Lakehouse/Warehouse, semantic models and data pipelines
Preferred: Power BI model metadata/TMDL and tools for inspecting DAX behaviour
Preferred: Semantic model performance analysis and data quality automation
Preferred: Telecom, subscription, sales or network reporting