Senior Analytics Engineer

Jobtailor

Jersey City (NJ)

On-site

USD 120,000 - 160,000

Full time

14 days+

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Job summary

Jobtailor seeks an experienced analytics engineer to design and implement scalable data models on BigQuery, leveraging dbt and AI-assisted workflows. You will own the semantic layer in Lightdash and define trusted metrics for the business.

Collaborate with cross-functional partners, advance governance, and enable self-serve analytics across the organization using Python, SQL, and CI/CD practices.

Qualifications

5+ years in analytics engineering or equivalent role.
Proficient with dbt and software engineering practices.
Experience with BigQuery or equivalent cloud warehouse.
Experience with Lightdash or similar BI tools.
Proficient in SQL and Python; familiar with CI/CD and testing.

Responsibilities

Design and build data models and transformations in dbt on BigQuery.
Own semantic layer in Lightdash with metrics and governed datasets.
Lead data modeling standards, reviews, and documentation.
Develop end-to-end with AI coding agents and AI-assisted workflows.
Enable AI-driven analytics with governance as foundation.
Advance metric governance and ensure auditability.
Partner with stakeholders to gather requirements and ship models.
Train users on self-serve analytics across the business.

Skills

Analytics engineer

dbt

Google BigQuery

SQL

Python

Data Governance

CI/CD

Testing

Tools

Lightdash

Looker

Claude Code

CI/CD Tools

Job description

Design and build our data models and transformations, applying software engineering best practices in dbt on top of our Google BigQuery warehouse to produce datasets that are accurate, performant, and easy to reason about.
Own the semantic layer in Lightdash, defining metrics, dimensions, and governed datasets so the business gets one consistent, trusted answer to every question - no matter who (or what) is asking.
Act as a leader for our data modeling standards, shaping conventions, review practices, and documentation that keep the transformation layer maintainable as it grows.
Develop end-to-end with AI coding agents. Our teams build with Claude Code and similar tools, and you'll use AI-assisted workflows to move faster while upholding quality through testing and review.
Enable AI-driven analytics, treating the semantic and governance layers as the foundation that agents and MCP connections build on to deliver trustworthy, self-serve answers from data.
Advance metric governance and definitional consistency, contributing to the auditability and reporting rigor expected of a company operating at scale and under growing scrutiny.
Partner with cross-functional stakeholders to gather requirements, identify high-value reporting and dashboarding use cases, and ship the models and metrics that drive decisions.
Train and enable users on self-serve analytics capabilities and best practices, growing the number of people across the business who can confidently answer their own questions with data.

Requirements

An experienced analytics engineer with 5+ years in analytics engineering, data engineering, or a similar role, with a proven ability to model data for reporting and analytics needs.
Highly experienced with dbt, applying the best practices of software engineering - modularity, testing, code review, documentation - to data transformation.
An expert in the modern data stack, with hands-on experience across cloud data warehousing (BigQuery or equivalent), data transformation, and workflow orchestration.
Experienced with a modern BI / semantic layer such as Lightdash, Looker, or similar - and opinionated on where the metrics layer is heading and why it matters more, not less, in an agentic world.
Fluent in AI-assisted development. You have real experience developing with Claude Code or a similar coding agent, or you're eager to make AI-driven workflows a core part of how you build.
Analytically minded. You have experience with or a strong interest in the analytical side of data - collecting requirements, defining and implementing metrics, and developing dashboards that tell a clear story.
A strong cross-functional partner. You build trust with stakeholders easily, translate business questions into well-modeled data, and communicate clearly with both technical and non-technical audiences.
Technically fluent. You're proficient in SQL and Python, with a strong working knowledge of software engineering workflow tools such as version control, CI/CD, and testing.

Core Competencies

Demonstrates expertise in data modeling and transformation using dbt and Google BigQuery, with a strong focus on metric governance and self-serve analytics. Proficient in SQL and Python, with experience in AI-assisted development and cross-functional collaboration.

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