Senior Analytics Engineer

Jellyfish

. Design and maintain analytical data models that transform raw engineering and product data into understandable, reusable datasets .

Posted 9/17/2026full-timeRemote • United StatesSenior💰 $150,000 - $230,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining analytical data models, with a strong focus on SQL, dbt, and data quality practices. Capable of collaborating with cross-functional teams to define metrics and improve data accessibility and usability.

Highest-signal resume keywords

Complex SQLDbt Transformation FrameworkDimensional ModelingData Quality MindsetSaaS Environment Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDimensional ModelingData Quality TestingData DocumentationData Transformation

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

DbtDatabricksDelta LakeOpenMetadata

Industry Keywords

SaaSData GovernanceData LineageAnalytical Data Models

Tech Stack

Tools & technologies

SQL

About the role

Key responsibilities & impact

Design and maintain analytical data models that transform raw engineering and product data into understandable, reusable datasets
Define facts, dimensions, metrics, and canonical business entities shared across the organization
Introduce and mature tools such as dbt for transformations, testing, documentation, and lineage
Establish maintainable analytical transformation patterns
Build automated checks for completeness, freshness, uniqueness, referential integrity, and other data-quality signals
Detect data problems closer to their source
Partner with Product, Engineering, and Analytics to define important metrics consistently across dashboards, APIs, and customer-facing experiences
Improve developer and analyst enablement through documentation, examples, reusable models, and data-flow guidance
Work in a collaborative, performance-driven team environment
Occasional travel may be required

Requirements

What you’ll need

Extremely comfortable working with complex SQL
Experience with dbt or similar transformation frameworks
Understanding of staging models, intermediate models, marts, testing, lineage, and semantic layers
Understanding of dimensional modeling, normalized and denormalized models, facts and dimensions, grain, and slowly changing dimensions
Data quality mindset, including tests, contracts, and documentation
Ability to work with engineers, analysts, product managers, and domain experts to define precise data concepts
Experience in a rapidly scaling SaaS environment (bonus)
Experience introducing dbt or an equivalent modeling framework into an existing data platform (bonus)
Experience with Databricks, Delta Lake, or lakehouse architectures (bonus)
Experience with data catalogs, lineage, or governance platforms like OpenMetadata (bonus)
Experience defining semantic models or metric contracts consumed by analytics and production applications (bonus)
Must be authorized to work for any employer in the US
Must be willing to work EST hours in your current time zone
Must not require current or future US employment visa sponsorship

Benefits

Comp & perks

Equity
Occasional travel opportunities