Senior Analytics Engineer

Jobtailor; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor is seeking an experienced analytics engineer to build canonical data models that serve as a single source of truth for the company. You will define and maintain core metrics across business lines and model data in dbt or equivalent tooling to power dashboards, self-serve analytics, and customer reports.

You will write tests, documentation, and data quality checks, create clear definitions for tables and fields, and reconcile metric definitions across teams.

Qualifications

• Expert-Level SQL and data modeling supporting reporting and decision-making.
• Established data models and reusable assets rather than ad-hoc queries.
• Defined, reconciled, or maintained business-critical metrics across teams.
• Collaborated with analysts, data scientists, operators, finance, product, and customer-facing teams.
• Debugged data quality issues, dashboard changes, metric discrepancies, and lineage problems.

Responsibilities

• Build canonical data models to create a shared source of truth across the company.
• Define and maintain core business, operational, financial, product, and customer-facing metrics.
• Model data in dbt or equivalent to enable dashboards, self-serve analytics, and customer reports.

Skills

SQL

Data Modeling

Analytics Engineering

Business Intelligence

Data Quality Checks

Metric Definition

Data Lineage

Debugging

Reporting Frameworks

Data Architecture

Tools

Dbt

BigQuery

Snowflake

Redshift

Databricks SQL

Job description

• Build canonical data models that create a shared source of truth across the company
• Define and maintain core business, operational, financial, product, and customer-facing metrics
• Model data in dbt or equivalent transformation tooling so dashboards, self-serve analytics, and customer reports pull from trusted tables
• Write tests, documentation, and data quality checks that catch issues before they reach users
• Create clear definitions for tables, fields, and metrics so teams understand what the data means and when to use it
• Reconcile metric definitions across internal teams, external reporting needs, and payer customer expectations
• Trace data lineage and debug dashboards, reports, or tables that change unexpectedly
• Partner with analysts, data scientists, operations, finance, product, engineering, and customer-facing teams to understand data needs and translate them into reliable models
• Help build reusable reporting frameworks that make onboarding new payers faster and less manual
• Partner with the data platform team to evolve warehouse tables, improve data architecture, and strengthen data contracts
• Improve warehouse cost, performance, and maintainability
• Support PHI-aware data access patterns and help ensure sensitive healthcare data is modeled and used responsibly

Requirements

• Built analytics engineering, business intelligence, or data modeling systems in a production cloud warehouse environment
• Written expert-level SQL and designed data models that support reporting, analysis, and decision-making
• Worked with dbt or an equivalent transformation framework
• Built tested, documented, reusable data models rather than one-off queries
• Defined, maintained, or reconciled business-critical metrics across teams
• Partnered with analysts, data scientists, operators, finance teams, product teams, or customer-facing stakeholders
• Debugged data quality issues, dashboard changes, metric discrepancies, and lineage problems
• Worked with cloud data warehouses such as BigQuery, Snowflake, Redshift, Databricks SQL, or similar
• Balanced speed, correctness, usability, and maintainability when building data assets
• Communicated clearly with technical and non-technical stakeholders about what data means and how it should be used.

Core Competencies

Expertise in building and maintaining data models, analytics engineering, and business intelligence systems in cloud environments, with a strong focus on SQL, dbt, and data quality assurance. Ability to collaborate with cross-functional teams to define metrics and ensure responsible use of sensitive data.

Highest-signal resume keywords

• Expert-Level SQL
• Data Modeling
• Dbt Transformation Framework
• Cloud Data Warehousing
• Data Quality Assurance

ATS Optimization Keywords

Hard Skills

• Data Modeling
• SQL
• Analytics Engineering
• Business Intelligence
• Data Quality Checks
• Metric Definition
• Data Lineage
• Debugging
• Reporting Frameworks
• Data Architecture

Soft Skills

• Clear Communication
• Collaboration

Industry Keywords

• Healthcare Data
• PHI-Aware Data Access
• Operational Metrics
• Customer-Facing Metrics
• Data Contracts

Tools & Technologies

• Dbt
• BigQuery
• Snowflake
• Redshift
• Databricks SQL