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Senior Analytics Engineer Jobs (NOW HIRING)

ROLE OVERVIEW As a Senior Analytics Engineer, you will own end-to-end analytics delivery - from well-governed dbt data models through to polished Tableau dashboards or AI solutions consumed by ...

Sr Analytics Engineer

Alpharetta, GA · On-site

$102K - $140K/yr

About the Senior Analytics Engineer Position The Senior Analytics Engineer is a key member of our Data Analytics team, responsible for designing, building, and maintaining scalable data and analytics ...

Senior Analytics Engineer

Austin, TX · Hybrid

$103K - $142K/yr

Senior Analytics Engineer Location: Austin, TX (hybrid) Schedule: Full-time | Hybrid (2-3 days in office) Work Authorization Notice: At this time, we are unable to provide immigration sponsorship for ...

As Senior Analytics Engineer, you will work alongside the Analytics and Visualization team and internal stakeholders to develop reporting solutions powered by our unique data pipeline. Successful ...

Senior Analytics Engineer

Seattle, WA · On-site

$118K - $163K/yr

They are seeking a Senior Analytics Engineer to design and implement large-scale data warehouses, build data transformation pipelines, and ensure data accessibility and actionability across the ...

Senior Analytics Engineer

Manhattan, NY · On-site +1

$115K - $158K/yr

Senior Analytics Engineer Orchard's mission is to make home buying and selling, stress free, fair and simple. For the average American, the home purchase and sale process takes months, creates ...

Sr Analytics Engineer

Alpharetta, GA · On-site

$102K - $140K/yr

About the Senior Analytics Engineer Position The Senior Analytics Engineer is a key member of our Data Analytics team, responsible for designing, building, and maintaining scalable data and analytics ...

Vida Health is seeking a Senior Analytics Engineer to serve as a high-impact, full-stack data partner. Positioned at the intersection of analytics engineering and data analysis, this role requires a ...

As a Senior Analytics Engineer , you will be a key architect of Robinhood's data foundation. You'll be responsible for the design and development of high-performance ETL pipelines, data models, and ...

ROLE OVERVIEW As a Senior Analytics Engineer, you will own end-to-end analytics delivery - from well-governed dbt data models through to polished Tableau dashboards or AI solutions consumed by ...

Senior Analytics Engineer

New York, NY · On-site

$147K - $184K/yr

About the Role As a Senior Analytics Engineer, you will be responsible for developing and optimizing our dbt infrastructure, implementing scalable data models, and ensuring consistent business logic ...

The Senior Analytics Engineer will be a foundational developer and force multiplier for fairlife's ambition to create a bestinclass Decision Intelligence (DI) ecosystem. This role will own the ...

About the Role As a Senior Analytics Engineer, you will be responsible for developing and optimizing our dbt infrastructure, implementing scalable data models, and ensuring consistent business logic ...

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Showing results 1-20

Senior Analytics Engineer information

See salary details

$59.5K

$126.6K

$183.5K

How much do senior analytics engineer jobs pay per year?

As of Jun 4, 2026, the average yearly pay for senior analytics engineer in the United States is $126,557.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $143,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Senior Analytics Engineer, and why are they important?

To thrive as a Senior Analytics Engineer, you need strong expertise in data modeling, SQL, data warehousing, and analytics, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools such as dbt, Python, cloud data platforms (like Snowflake or BigQuery), and experience with BI tools are commonly required, along with certifications in analytics or cloud technologies being a plus. Excellent problem-solving, communication, and stakeholder management skills help you translate business requirements into robust data solutions. These skills ensure data integrity, drive actionable insights, and support effective decision-making across the organization.

How does a Senior Analytics Engineer typically collaborate with data scientists and business stakeholders?

Senior Analytics Engineers play a vital role in bridging the gap between raw data and actionable insights. They work closely with data scientists to ensure that data pipelines and models are robust, scalable, and well-documented. Additionally, they frequently meet with business stakeholders to understand reporting needs and translate them into technical requirements, ensuring that analytics solutions align with organizational goals. This collaborative approach helps maintain data quality and accelerates the delivery of meaningful analyses across teams.

What is a Senior Analytics Engineer?

A Senior Analytics Engineer is a data professional who bridges the gap between data engineering and data analysis. They design, build, and maintain data pipelines, data models, and analytics infrastructure to ensure that data is reliable, accessible, and well-structured for analysis. Typically, they work with tools like SQL, dbt, and cloud data warehouses, collaborating closely with data analysts and business stakeholders to deliver actionable insights. Their role often involves optimizing data workflows, implementing best practices, and mentoring junior team members.

What is the difference between Senior Analytics Engineer vs Data Engineer?

AspectSenior Analytics EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, Analytics, or related; SQL, Python, data visualization skillsBachelor's/Master's in CS, Data Engineering, or related; SQL, Python, ETL tools skills
Work EnvironmentFocus on data analysis, reporting, and insights; collaborates with data teams and business unitsFocus on data pipeline development, infrastructure, and storage; works closely with data infrastructure teams
Employer & Industry UsageUsed across tech, finance, healthcare, and retail for analytics rolesCommon in tech, finance, and data-driven industries for building data systems

While both roles require strong SQL and Python skills, Senior Analytics Engineers primarily focus on analyzing data, creating reports, and deriving insights for business decisions. Data Engineers build and maintain the data infrastructure, pipelines, and storage systems. The roles often collaborate but serve different functions within data teams.

More about Senior Analytics Engineer jobs
What cities are hiring for Senior Analytics Engineer jobs? Cities with the most Senior Analytics Engineer job openings:
What are the most commonly searched types of Analytics Engineer jobs? The most popular types of Analytics Engineer jobs are:
What states have the most Senior Analytics Engineer jobs? States with the most job openings for Senior Analytics Engineer jobs include:
Infographic showing various Senior Analytics Engineer job openings in the United States as of May 2026, with employment types broken down into 82% Full Time, 15% Part Time, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $126,557 per year, or $60.8 per hour.
Senior Analytics Engineer

Senior Analytics Engineer

SolarWinds

Austin, TX • On-site

Other

Posted 14 days ago


SolarWinds rating

8.9

Company rating: 8.9 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

26th of 185 rated software companies


Job description

ROLE OVERVIEW

As a Senior Analytics Engineer, you will own end-to-end analytics delivery - from well-governed dbt data models through to polished Tableau dashboards or AI solutions consumed by business leaders across Revenue, Customer Success, and Product.

This is a high-impact individual contributor role with balanced accountability across transformation and delivery. You'll spend roughly half your time on dbt model development and half on Tableau dashboard delivery and business stakeholder engagement - the bridge between our Analytics Engineering platform and the business teams who rely on it. You'll collaborate closely with our AE community in Austin and the Philippines, aligning data models and metrics to real business requirements.

The right candidate is equally comfortable writing production-grade dbt SQL and sitting with a senior stakeholder to translate a business question into a data product. You bring craft to both sides of that equation.

This is a highly autonomous role within a rapidly evolving analytics function. Success will require curiosity, initiative and the ability to bring structure, energy, and innovative thinking to ambiguous problem.

KEY RESPONSIBILITIES

  • Design, build, and maintain dbt data models (Staging, Intermediate, Mart layers) following SolarWinds modelling standards, with a focus on consumption-ready, well-tested data products
  • Deliver high-quality Tableau dashboards and self-serve analytics assets for business teams across Revenue, Customer Success, Finance, and Product - from requirements through to stakeholder sign-off
  • Own the Tableau-to-dbt integration layer: consume MetricFlow semantic layer definitions in Tableau Cloud, ensuring metrics are consistent, governed, and aligned with company-wide standards
  • Partner directly with stakeholders across assigned business domains to translate ambiguous business problems into scalable analytical solutions, proactively identifying gaps in requirements, aligning stakeholders, and driving clarity on metrics, logic and desired outcomes
  • Champion data quality - write dbt tests, enforce delivery SLAs, and embed lineage documentation as standard practice
  • Lead and run CI/CD processes for your dbt models - branch-based development, PR reviews, and automated test gates
  • Support and mentor junior and mid-level analysts, promoting best practices in SQL, dbt modelling, and Tableau development
  • Contribute to the rollout of self-serve analytics enablement programmes for business users, reducing dependency on direct analyst requests

REQUIRED SKILLS & EXPERIENCE

  • 5+ years of experience in analytics engineering, business intelligence, or a related data role
  • Production-grade dbt experience (dbt Core or dbt Cloud) - you've designed and maintained multi-layer models at scale, written macros, and contributed to shared packages
  • Advanced Tableau expertise - including development or performant, governed and user-friendly analytical solutions integrated with modern semantic layer & with the ability to clearly explain modelling, metric and design decisions with stakeholders
  • Python proficiency for analytics use cases - data wrangling, scripting, custom dbt macros, or exploratory analysis
  • Strong SQL fundamentals - complex analytical queries, window functions, CTEs, aggregations, and query performance awareness
  • Experience with a modern cloud data warehouse (BigQuery, Snowflake, or Redshift) including understanding of materialisation and performance trade-offs
  • Git and branch-based development workflows - you treat analytics code with software engineering discipline
  • CI/CD experience in a data context - dbt test gates, PR-triggered runs, or equivalent pipeline automation
  • Solid understanding of data modelling concepts - star schema, slowly changing dimensions, metric normalisation
  • Strong communication skills - you can present data findings to non-technical audiences and translate vague business questions into clear model briefs

NICE TO HAVE

  • Hands-on MetricFlow or dbt Semantic Layer experience in a production environment
  • Familiarity with the Tableau + dbt Cloud connector (Tableau 2025.2+) for semantic layer consumption
  • Familiarity with Salesforce or NetSuite as source systems
  • Experience in a SaaS or recurring revenue business - ARR, churn, expansion, and NRR metrics
  • Exposure to Dataplex, Fivetran, or similar data cataloguing and ELT tooling
  • Experience with next-generation self-serve BI platforms (Omni, Looker, ThoughtSpot) - we are actively evaluating alongside Tableau
  • Working knowledge of GDPR data residency requirements in an analytics context
  • Comfort using AI coding assistants and LLM-based tools in analytics workflows