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Analytics Engineer Jobs in Carlsbad, CA (NOW HIRING)

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging ...

Senior Analytics Engineer

Carlsbad, CA · On-site

$119K - $188K/yr

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging ...

Senior Analytics Engineer

Carlsbad, CA · On-site

$119K - $188K/yr

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging ...

Senior Analytics Engineer

Carlsbad, CA · On-site

$148K - $222K/yr

What you'll do As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging ...

Unblock teams on access, metric definitions, and data discoverability as part of a broader effort to reduce reliance on you as a bottleneck Required * 6+ years in analytics engineering, data ...

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Analytics Engineer information

See Carlsbad, CA salary details

$62.9K

$109.8K

$179K

How much do analytics engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for analytics engineer in Carlsbad, CA is $109,772.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,975.00 and $123,214.00 per year, depending on experience, location, and employer.

What is an analytics engineer?

An Analytics Engineer is a professional who bridges the gap between data engineering and data analysis. They are responsible for designing, building, and maintaining data models, pipelines, and analytics tools that enable organizations to make data-driven decisions. Analytics Engineers often work closely with data analysts and business stakeholders to ensure clean, reliable, and well-structured data is available for reporting and analysis. Their work typically involves using SQL, data transformation tools like dbt, and cloud data warehouses to create scalable and efficient data solutions.

How does an analytics engineer typically collaborate with data scientists and business stakeholders on projects?

Analytics Engineers play a critical bridge role between data engineering and data analysis. They work closely with data scientists to transform raw data into clean, reliable datasets that are ready for advanced analytics or modeling. At the same time, they collaborate with business stakeholders to understand reporting needs, ensuring that data models align with business goals. Regular communication and iterative feedback are key, as Analytics Engineers often gather requirements, build data pipelines, and adjust data products based on stakeholder input.

What are the key skills and qualifications needed to thrive as an analytics engineer, and why are they important?

To thrive as an Analytics Engineer, you need a strong foundation in data modeling, SQL, and analytics engineering principles, often supported by a degree in computer science, data science, or a related field. Proficiency with data transformation tools such as dbt, cloud data warehouses like Snowflake or BigQuery, and version control systems like Git is essential. Strong problem-solving skills, communication, and collaboration abilities help translate business needs into scalable data solutions and foster teamwork. These skills and qualities are crucial for ensuring data quality, building reliable analytics infrastructure, and enabling data-driven decision-making across organizations.

What is the difference between Analytics Engineer vs Data Engineer?

AspectAnalytics EngineerData Engineer
CredentialsOften requires SQL, Python, data modeling certificationsRequires similar skills, often with additional focus on infrastructure and systems
Work EnvironmentFocuses on data analysis, visualization, and reportingBuilds data pipelines, manages data infrastructure
Industry UsageCommon in analytics teams, BI, and data-driven rolesPrevalent in data engineering, data platform teams

While both roles work closely with data, Analytics Engineers primarily focus on transforming data for analysis and visualization, whereas Data Engineers build the infrastructure and pipelines that enable data access. Understanding these differences helps in choosing the right career path or job role.

Do analytics engineers make good money?

Analytics engineers typically earn competitive salaries that vary by experience, location, and industry. They often have skills in SQL, data modeling, and tools like Python or Spark, which can contribute to higher compensation. Overall, the role is considered well-paying within the data and analytics field.

What do analytics engineers do?

Analytics engineers design, build, and maintain data pipelines and infrastructure to enable data analysis and reporting. They work with tools like SQL, Python, and data warehouses to ensure data is accurate, accessible, and well-structured for business insights.

What are the most commonly searched types of Analytics Engineer jobs in Carlsbad, CA?

The most popular types of Analytics Engineer jobs in Carlsbad, CA are:

What are popular job titles related to Analytics Engineer jobs in Carlsbad, CA?

For Analytics Engineer jobs in Carlsbad, CA, the most frequently searched job titles are:

What job categories do people searching Analytics Engineer jobs in Carlsbad, CA look for?

The top searched job categories for Analytics Engineer jobs in Carlsbad, CA are:

What cities near Carlsbad, CA are hiring for Analytics Engineer jobs?

Cities near Carlsbad, CA with the most Analytics Engineer job openings:

Infographic showing various Analytics Engineer job openings in Carlsbad, CA as of August 2026, with employment types broken down into 82% Full Time, 4% Part Time, and 14% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $109,772 per year, or $52.8 per hour.

Senior Analytics Engineer

Viasat, Inc.

Carlsbad, CA

$148K - $222K/yr

Full-time

Re-posted 14 days ago


Viasat rating

7.0

Company rating: 7.0 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

69th of 101 rated telecommunications companies


Job description

About us

One team. Global challenges. Infinite opportunities. At Viasat, we’re on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate. We’re looking for people who think big, act fearlessly, and create an inclusive environment that drives positive impact to join our team.


What you'll do

As a Senior Analytics Engineer, you will own and extend our demand forecasting platform, modeling satellite bandwidth requirements across Maritime, Aviation, Enterprise, and emerging Direct-to-Device (D2D) markets. You'll translate executive-level business questions into scalable data pipelines and geospatial models, driving iterative cycles of data interpretation and assumption refinement. You'll turn ambiguous forecasting challenges into production-quality analytical tools—and just as importantly, help senior leadership understand what the data is (and isn't) telling them.
Reporting to the Director, Commercial Business Analytics, you'll operate at the intersection of business strategy and data engineering—close enough to executive stakeholders to shape the why behind the models, and close enough to engineering to ensure your work can be productionized and scaled. Your forecasting outputs feed directly into capacity feasibility analyses run by engineering teams, making the handoff relationship critical.


The day-to-day
  • Partner directly with business unit executives and C-level stakeholders to translate strategic forecasting needs into data models, proactively surfacing insights and challenging assumptions
  • Own and evolve demand forecasting pipelines using Python, SQL, and modern orchestration tools (Dagster, dbt, BigQuery)
  • Develop and extend geospatial demand models using GIS tooling (H3, PostGIS, Kepler.gl, GeoPandas) to translate global market opportunity into demand projections for targeted geographies
  • Drive forecasting model expansion to new business units and services through configurable, testable code—often where no existing baseline exists
  • Independently validate model outputs, refine assumptions, and recommend adjustments to input parameters based on observed patterns and business feedback
  • Interpret and present forecasting outputs in business context to senior leadership—identifying where model results challenge assumptions, surfacing data quality risks, and advising on methodology changes
  • Evaluate and integrate 3rd-party industry data to assess total global vertical demand and model geographic distribution
  • Build data structures with engineering handoff in mind—balancing analytical flexibility with the conventions and standards that enable smooth transition to production systems
  • Document methodologies, assumptions, and maintain clear data lineage across all forecasting workstreams
  • Deliver regional and scenario-based demand projections that directly inform capacity planning decisions
  • Collaborate with engineering teams who consume forecasting outputs, ensuring data formats, assumptions, and methodologies are well-documented and aligned with downstream systems
  • Continuously evaluate existing forecasting processes and recommend improvements to enhance accuracy, scalability, and stakeholder confidence

What you'll need
  • Bachelor's degree in a quantitative field
  • 5–8 years of experience in analytics engineering, data engineering, or quantitative analysis
  • Demonstrated experience managing executive and cross-functional stakeholder relationships—translating complex analytical outputs into actionable business guidance
  • Hands-on GIS and geospatial analysis experience (e.g., H3, PostGIS, GeoPandas, Kepler.gl, or equivalent tooling)
  • Strong SQL and cloud data warehouse experience (BigQuery preferred)
  • Python proficiency with data engineering and analytical libraries (pandas, scipy, etc.)
  • Proven ability to structure ambiguous business problems into well-defined analytical frameworks
  • Experience building maintainable, scalable data pipelines with clear documentation and lineage
  • Strong written and verbal communication skills, including experience presenting to senior leadership
  • Comfort owning outcomes in fast-paced, evolving environments with minimal supervision

What will help you on the job
  • Master's degree or equivalent experience in a quantitative field
  • Experience transitioning analytical models into production infrastructure alongside engineering teams
  • Satellite or telecom industry experience
  • Hands-on experience with Dagster, Airflow, or dbt
  • Demand forecasting or capacity planning experience
  • Familiarity with spatial statistics, coverage modeling, or network planning tools

Salary range
$119,000.00 - $188,500.00 / annually.For specific work locations within San Jose, the San Francisco Bay area and New York City metropolitan area, the base pay range for this role is $148,500.00- $222,500.00/ annually
At Viasat, we consider many factors when it comes to compensation, including the scope of the position as well as your background and experience. Base pay may vary depending on job-related knowledge, skills, and experience. Additional cash or stock incentives may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered. Learn more about Viasat's comprehensive benefit offerings that are focused on your holistic health and wellness at https://careers.viasat.com/benefits.
EEO Statement

Viasat is proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, ancestry, physical or mental disability, medical condition, marital status, genetics, age, or veteran status or any other applicable legally protected status or characteristic. If you would like to request an accommodation on the basis of disability for completing this on-line application, please click here.

Qualifications:
  • Bachelor's degree in a quantitative field
  • 5–8 years of experience in analytics engineering, data engineering, or quantitative analysis
  • Demonstrated experience managing executive and cross-functional stakeholder relationships—translating complex analytical outputs into actionable business guidance
  • Hands-on GIS and geospatial analysis experience (e.g., H3, PostGIS, GeoPandas, Kepler.gl, or equivalent tooling)
  • Strong SQL and cloud data warehouse experience (BigQuery preferred)
  • Python proficiency with data engineering and analytical libraries (pandas, scipy, etc.)
  • Proven ability to structure ambiguous business problems into well-defined analytical frameworks
  • Experience building maintainable, scalable data pipelines with clear documentation and lineage
  • Strong written and verbal communication skills, including experience presenting to senior leadership
  • Comfort owning outcomes in fast-paced, evolving environments with minimal supervision
Education:UNAVAILABLEEmployment Type: FULL_TIME

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ViaSat logo

About ViaSat

Sourced by ZipRecruiter

At Viasat, we're on a mission to deliver connections with the capacity to change the world. For more than 35 years, Viasat has helped shape how consumers, businesses, governments and militaries around the globe communicate.

Industry

Telecommunications

Company size

5,001 - 10,000 Employees

Headquarters location

Carlsbad, CA, US

Year founded

1986