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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Proficient in designing and maintaining analytical data models for FinOps, with strong skills in SQL and Python for data transformation and reporting. Experienced in building ingestion pipelines and collaborating with cross-functional teams to ensure data quality and reliable AI outputs.
Highest-signal resume keywords
Strong SQL SkillsPython ProficiencyExperience With Analytical DatabasesLLM API Development ExperienceFamiliarity With MCP
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonData TransformationData NormalizationAnalytical DatabasesLLM API DevelopmentData ModelingQuery Performance OptimizationData Quality ImprovementPrompt Engineering
Soft Skills
CollaborationProblem-SolvingAttention To DetailAdaptability
Tools & Technologies
AWSAzureMetabaseClickHouseBigQueryRedshiftDuckDBMCP
Industry Keywords
FinOpsCost AllocationAnomaly DetectionInfrastructure UsageUnit Economics
Tech Stack
Tools & technologiesAmazon RedshiftAWSAzureBigQueryCloudPythonSQL
About the role
Key responsibilities & impact- Design and maintain analytical data models for FinOps data, including cloud cost, cost allocation, anomaly signals, infrastructure usage, and unit economics.
- Build ingestion and normalization pipelines for AWS and Azure billing, SaaS platforms, product telemetry, and internal systems.
- Develop AI-powered reporting skills in Python using MCP that return structured answers to stakeholder questions.
- Implement prompt engineering and output validation layers for trustworthy AI-generated answers.
- Build and maintain Metabase dashboards covering FinOps metrics and additional domains.
- Collaborate with FinOps experts, product managers, and domain leads to translate requirements into data models and query patterns.
- Help evaluate and contribute to architecture decisions for new data domains and source systems.
- Document data models, AI skill patterns, and pipeline logic.
- Improve data quality, query performance, and AI output reliability as the platform scales.
Requirements
What you’ll need- Strong SQL skills — complex aggregations, window functions, joins across large datasets, and the instinct to investigate when a number looks wrong before shipping.
- Python proficiency — clean, maintainable scripts for data transformation, normalization, and tooling (not just notebooks).
- Experience with analytical or columnar databases — such as ClickHouse, BigQuery, Redshift, DuckDB, or similar.
- Demonstrated experience building with an LLM API (Anthropic, OpenAI, or similar) — understanding tool use, structured outputs, and reliable AI responses.
- Ability to work from well-defined requirements and translate a subject matter expert’s question into an accurate data model and query.
- Comfort in a greenfield environment and ability to make sound architectural decisions when patterns are still being established.
- Familiarity with MCP (Model Context Protocol) or similar function-calling / tool-use patterns for LLMs (preferred).
Benefits
Comp & perks- Attractive compensation – including competitive base pay and performance-based variable pay.
- Equity/Stock in Intapp.
- Opportunity to travel to other development centers for product training and cross-site collaboration.
- One-time home office stipend.
- Generous paid parental leave (including adoptive leave), marriage leave, bereavement leave, carer's leave, and paid sick days.
- Reimbursement for training towards continuing education.