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Posted: 10/14/2026Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in SQL for querying and analyzing complex datasets, alongside hands-on experience with Databricks for data validation and troubleshooting. Proficient in data reconciliation, root cause analysis, and effective communication with cross-functional teams to enhance customer experience.
Highest-signal resume keywords
Strong SQL SkillsDatabricks ExperienceData Validation and ReconciliationRoot Cause AnalysisData Warehouse Design
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Act as the primary technical liaison between Customer Success and Engineering teams to expedite resolution of complex data-related issues
- Execute the Trace protocol through detailed log-level investigations and data validation within Databricks
- Analyze and reconcile data discrepancies across media platforms, DSPs, and internal systems
- Validate client configurations, integrations, and platform setups
- Execute engineering-defined runbooks for data reprocessing, synchronization, and recovery
- Perform root cause analysis of data anomalies and provide actionable findings
- Monitor data flows, pipelines, and synchronization processes for accuracy and completeness
- Create contextualized defect packages with logs, analysis results, reproduction steps, and evidence
- Triage and classify technical issues and route them to appropriate engineering teams or technical pods
- Collaborate with Engineering, Product, and Customer Success to reduce Time-to-Resolution and improve customer experience
- Develop and enhance troubleshooting documentation, runbooks, and knowledge base articles
- Identify recurring data quality issues and recommend process improvements, automation, and preventive measures
- Support incident investigations and post-mortem activities with detailed data analysis and technical insights
- Serve as a technical subject matter expert in data reconciliation, system diagnostics, and operational troubleshooting
Requirements
What you’ll need- Strong SQL skills, with the ability to query, analyze, validate, and reconcile complex datasets
- Hands-on experience with Databricks for data investigation, validation, and troubleshooting
- Understanding of data warehousing concepts, data flows, and ETL processes
- Ability to investigate data discrepancies, analyze logs, identify anomalies, and perform root cause analysis
- Experience with data validation, reconciliation, and troubleshooting across multiple systems or platforms
- Ability to analyze technical issues, document findings, and prepare clear, evidence-based defect reports for engineering teams
- Strong analytical and problem-solving skills, with attention to detail and a focus on data accuracy
- Effective communication and collaboration skills to work with cross-functional teams, including Engineering, Product, and Customer Success
- Ability to follow technical procedures and runbooks, manage escalations, and support incident investigations
- Good documentation skills, with the ability to develop and maintain troubleshooting guides, runbooks, and knowledge base articles
- Experience with data warehouse design and architecture
- Familiarity with ETL processes, data pipeline monitoring, and data synchronization
- Experience with data reprocessing, recovery procedures, or production incident troubleshooting
- Exposure to media platforms, demand-side platforms (DSPs), or integrations across multiple data systems
Benefits
Comp & perks- Employees can work remotely
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLData ValidationData ReconciliationRoot Cause AnalysisData Pipeline MonitoringETL ProcessesData SynchronizationData InvestigationData TroubleshootingData Analysis
Soft Skills
Analytical SkillsProblem-Solving SkillsAttention to DetailEffective CommunicationCollaboration Skills
Tools & Technologies
Databricks
Industry Keywords
Data WarehousingMedia PlatformsDemand-Side PlatformsIncident InvestigationsTechnical Documentation