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Data Analytics Jobs in Oxnard, CA (NOW HIRING)

AmaWaterways, LLC

Data Analytics Engineer

Calabasas, CA · On-site

$90K - $100K/yr

Role Summary AmaWaterways is hiring a Data Analytics Engineer to own the analytics layer of our modern data platform. You will design governed data marts, build the semantic layer that powers our ...

The Trade Desk

Data Support Analyst I

Ventura, CA · On-site

Bachelor's degree or relevant work experience (0-3 years); a background in data, analytics, marketing technology, or a related field is a plus. * Brings a collaborative and energetic mindset to the ...

KBR

Data Engineer

Camarillo, CA · On-site

$116K - $140K/yr

Title: Data Engineer Belong. Connect. Grow. with KBR! KBR's National Security Solutions team ... Analytic Experience: Candidate will be a part of the technical team responsible for providing ...

KBR, Inc.

Data Engineer

Camarillo, CA · On-site

$116K - $140K/yr

Title: Data Engineer Belong. Connect. Grow. with KBR! KBR's National Security Solutions team ... Analytic Experience: Candidate will be a part of the technical team responsible for providing ...

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All JobsData Analytics JobsData Analytics Jobs in Oxnard, CA

Data Analytics information

See Oxnard, CA salary details

$25

$57

$100

How much do data analytics jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for data analytics in Oxnard, CA is $57.98, according to ZipRecruiter salary data. Most workers in this role earn between $46.59 and $65.67 per hour, depending on experience, location, and employer.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, creating reports, and developing data models using tools like SQL, Excel, and Python or R. Strong analytical skills and knowledge of data visualization are essential for these positions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data specialist, or reporting analyst, focusing on collecting, processing, and analyzing data to support decision-making. They often use tools like Excel, SQL, and data visualization software, and may work in industries like finance, healthcare, marketing, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is the work for a data analytics?

A data analyst's work involves collecting, processing, and analyzing data to identify trends, support decision-making, and improve business outcomes. They use tools like Excel, SQL, and data visualization software, and often require strong analytical skills and attention to detail.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

What are the key skills and qualifications needed to thrive as a data analytics professional, and why are they important?

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.
What are the most commonly searched types of Data Analytics jobs in Oxnard, CA? The most popular types of Data Analytics jobs in Oxnard, CA are:
What job categories do people searching Data Analytics jobs in Oxnard, CA look for? The top searched job categories for Data Analytics jobs in Oxnard, CA are:
What cities near Oxnard, CA are hiring for Data Analytics jobs? Cities near Oxnard, CA with the most Data Analytics job openings:
Data Analytics jobs near you
Infographic showing various Data Analytics job openings in Oxnard, CA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $120,589 per year, or $58 per hour.

Data Analytics Engineer

AmaWaterways, LLC

Calabasas, CA • On-site

$90K - $100K/yr

Full-time

Re-posted 3 days ago

Job description

At AmaWaterways, we believe meaningful careers begin with purpose, passion and a shared commitment to delivering unforgettable experiences. For those who value curiosity, connection and personal enrichment, AmaWaterways offers the opportunity to help craft meaningful river journeys that invite travelers to follow their own current. Built on a foundation of heartfelt hospitality, we treat our guests—and each other—with genuine care, warmth and respect. AmaWaterways fosters a collaborative environment both onboard our ships and across our global network of offices, where team members grow together, support one another and take pride in upholding the high standards and thoughtful service our company is known for.

We invite talented, motivated professionals to explore our career opportunities and begin their journey with AmaWaterways today.

Role Summary

AmaWaterways is hiring a Data Analytics Engineer to own the analytics layer of our modern data platform. You will design governed data marts, build the semantic layer that powers our scorecards, and partner directly with Finance, Marketing, Revenue Management, Operations, and Reservations to turn ambiguous business questions into trusted models and dashboards. You will work on top of a Snowflake-native warehouse that is actively being built out, alongside a Senior Data Engineer who owns the ingestion plumbing. You will apply software engineering practices to analytics: version control, dbt tests, CI/CD, and clear documentation. You will also be an AI-native practitioner. Our daily environment is Claude Code, Snowflake Cortex, and dbt Cloud, and we expect you to use them fluently, not curiously.

What You Will Build
  • Governed semantic models in dbt for our top business KPIs: bookings, occupancy, revenue, cancellations, retention, marketing performance, and operations metrics.
  • Marts and reporting views on top of our medallion warehouse (Bronze, Silver, Gold, Reporting), with strict typing and clear grain documentation.
  • Tableau and Power BI assets that share a single source of truth in the warehouse. No off-platform calculations.
  • Cortex Analyst semantic YAML for natural-language data exploration by our internal users.
  • Data quality tests on every model you author, with clear ownership of the freshness and accuracy SLAs.
  • Companion views for the AMA Pulse scorecard (currently 72 KPIs across 894,000 rows of historical sailings).
  • BI assets that consolidate analytical work currently spread across the AMA Pulse Streamlit app, Tableau Cloud, and ad-hoc SQL.
Day to Day Responsibilities

Modeling and SQL

  • Build dbt models in our medallion layout. Use staging, intermediate, and mart models with explicit grain. Use SCD2 snapshots where business questions span time.
  • Write performant SQL in Snowflake. Read query profiles when something is slow. Use clustering and warehouse sizing deliberately.
  • Apply consistent naming conventions and audit columns across every mart.

Semantic layer and metric governance

  • Define metrics in the dbt Semantic Layer with explicit dimensions, time grains, and ownership.
  • Author Cortex Analyst semantic YAML for the marts that internal teams query through natural language.
  • Maintain a single canonical definition for every business KPI. No duplicate metric logic across Tableau, Power BI, and Streamlit.

BI development and governance

  • Build, optimize, and govern dashboards in Tableau Cloud and Power BI.
  • Implement row-level and object-level security, usage monitoring, and deployment workflows.
  • Audit and modernize legacy BI assets. Retire reports that nobody opens.

Data quality and reliability

  • Write dbt tests on every model: not-null, unique, relationships, accepted values, and custom business rules.
  • Add freshness checks and Snowflake Alerts to your gold and reporting models.
  • Track SLAs for the marts that feed leadership-facing reporting.

Stakeholder partnership

  • Translate ambiguous requests from Finance, Marketing, Revenue Management, Operations, and Reservations into models the rest of the team can also build on.
  • Write the kind of documentation your future self will want to read.
  • Partner with the Senior Data Engineer to make sure the source pipelines you depend on are designed correctly upstream.

AI-native analytics engineering

  • Use Claude Code as your primary working environment, including our shared data-team-skills plugin library.
  • Use Snowflake Cortex (Complete, Search, Analyst) to build natural-language interfaces, summarize text columns, classify free-text, and accelerate exploratory analysis.
  • Use multi-model review through zen-mcp when you are designing a new metric definition or auditing a complex SQL refactor.
Required Qualifications
  • 4+ years building governed analytics models and BI assets in a modern data warehouse.
  • Strong SQL on Snowflake. You can write window functions, recursive CTEs, and incremental MERGE patterns without searching the docs.
  • Production dbt experience: models, tests, snapshots, documentation, and CI runs.
  • Tableau (required) and Power BI (strongly preferred) at production quality, including parameterized dashboards, row-level security, and performance tuning on Snowflake-backed extracts or live connections.
  • Git and GitHub workflows with code review discipline.
  • You already use Claude Code, Cursor, or equivalent agent tooling daily, with concrete examples of what you ship faster because of it.
  • Strong written communication. You can explain a metric definition to a Finance leader and a SQL pattern to an engineer in the same week.
Strongly Preferred
  • dbt Semantic Layer.
  • Snowflake Cortex Analyst or Cortex Search in production.
  • GitHub Actions CI/CD for dbt projects.
  • Python for data work (pandas, snowflake-snowpark-python, ad-hoc scripting).
  • Domain experience in travel, hospitality, cruise, or consumer finance.
Nice to Have
  • Streamlit in Snowflake.
  • Salesforce Data Cloud or Salesforce Marketing Cloud reporting.
  • Power Automate flows for alert and notification routing.
  • Familiarity with Seaware, Oracle, or other reservation system data models.
  • Finance domain depth: revenue recognition, occupancy denominators, AOP targets.