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Analytics Engineer Jobs (NOW HIRING)

ABOUT THE ROLE: We're hiring an Analytics Engineer to help design and build a PBM Financial Risk Engine that brings together claims, contract terms, pricing and utilization data to support financial ...

Analytics Engineer This role will build out foundational agentic data tooling to support sales analytics and operations. As an Analytics Engineer at Podium you will be responsible for the ...

Analytics Engineer Full-time 4 days on-site in Charlotte, NC office Summary: Our client is hiring an Analytics Engineer The ideal candidate will act as the vital bridge between raw data and executive ...

About the Team The Analytics Engineering team at DoorDash is embedded within the Analytics and Data Engineering Orgs, and is responsible for building internal data products that scale decision-making ...

Analytics Engineer

New York, NY · On-site

$120K - $160K/yr

Qualifications • BS or MS in Engineering, Computer Science, Statistics, or related quantitative field. • 4+ years of experience in data science, engineering, analytics, or forecasting in a ...

Analytics Engineer RemoteFinanceFull time Nashville, Tennessee, United States Overview Application Description Role Overview We are hiring a United States based Analytics Engineer to support ...

Analytics Engineer Location : Philadelphia, PA Duration : long Job Summary A highly experienced analytics engineer with experience of working with large-scale, distributed data pipelines, you will be ...

Analytics Engineer

Edwardsville, IL · On-site

$107K - $129K/yr

Midwest Railcar - Analytics Engineer About the Role The Analytics Engineer builds and maintains the foundational data infrastructure that transforms raw business data into reliable, analysis-ready ...

Analytics Engineer

Edwardsville, IL

$107K - $129K/yr

Midwest Railcar - Analytics Engineer About the Role The Analytics Engineer builds and maintains the foundational data infrastructure that transforms raw business data into reliable, analysis-ready ...

Analytics Engineer I

New York, NY · Hybrid

$106K - $140K/yr

We're hiring an Analytics Engineer I to join our Data Team. Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We ...

Analytics Engineer

$80 - $100/hr

Lead Analytics Engineer / Delivery Lead Client Location: McLean, VA Work Location: Remote (USA) Duration: Long Term Rate: Quote your best Required Qualifications: * At least 10+ years extensive ...

This is MLG's first-ever Analytics Engineer hire, supporting the modernization of reporting, analytics, and data operations across the firm. Role Overview This role is designed as a modern hybrid ...

As a Senior Analytics Engineer, you will be a key contributor in helping the organization derive more value from its datasets through scalable, modular design of our enterprise data models and ...

Analytics Engineer

New York, NY · Remote

$125K - $215K/yr

Role Overview We are looking for a talented and passionate Analytics Engineer to join our team. In this role, you will be responsible for designing, building, and maintaining data infrastructure to ...

Analytics Engineer We're hiring an Analytics Engineer to sit at the intersection of data engineering and analytics. This is a high-impact, zero-to-one role where you'll help build the analytics ...

Analytics Engineer

$95K - $190K/yr

Metabase is looking for an Analytics Engineer to support our team. This role will be a key part of the operations team, using the disparate data sources we have on our customer base, customer ...

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Analytics Engineer information

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$62.5K

$109.1K

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How much do analytics engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for analytics engineer in the United States is $109,135.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,500.00 and $122,500.00 per year, depending on experience, location, and employer.

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 engineers make $500,000?

Senior-level engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

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.

What is the average salary of an analytics engineer?

The average salary of an analytics engineer typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals with skills in SQL, Python, and data visualization tools tend to earn higher salaries, especially in larger organizations or tech hubs.

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 is big data salary?

The salary for an Analytics Engineer working with big data typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals skilled in tools like Hadoop, Spark, and SQL tend to earn higher salaries, especially with certifications and advanced technical expertise.

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.
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Analytics Engineer

$140K/yr

Other

Posted 13 days ago


Job description

ABOUT THE ROLE:

We're hiring an Analytics Engineer to help design and build a PBM Financial Risk Engine that brings together claims, contract terms, pricing and utilization data to support financial forecasting, risk assessment and performance monitoring. This role is ideal for someone who is strong in dbt and analytics engineering and who enjoys working at the intersection of healthcare economics, PBM operations and data modeling. The ideal candidate will play a pivotal role in developing and maintaining our financial risk engine data models, onboarding new data sources and optimizing existing data sources and packaging the data in a way that promotes seamless reporting while paving a way for innovation through advanced analytics. This role will involve delivering and analyzing PBM financial data for various analytics use cases within our Unified Data Warehouse (UDW) and productionalizing AI and ML solutions through the curated data to drive impactful healthcare insights.

WHAT YOU'LL DO:

  • Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems using PBM data.
  • Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM financial risk engine, leveraging claims, eligibility, pricing, rebates, guarantees and contract data in our Unified Data Warehouse (UDW).
  • Translate complex PBM contract and pricing structures (e.g plan paid vs. member paid, rebates, guarantees, caps, fees, exclusions) into transparent, auditable data models that enable financial analysis and risk assessment.
  • Partner closely with underwriting, finance, client success and PBM operations teams to understand financial assumptions, risk drivers and reporting requirements and convert them into reliable metrics and models.
  • Build curated financial and risk data marts and semantic layers that enable self service analysis for forecasting, scenario modeling and executive reporting among other things.
  • Own core financial KPIs and risk metrics E2E from raw claims and contract inputs through production grade models, ensuring consistency and traceability.
  • Implement automated data quality checks, reconciliations and controls to validate financial outputs and ensure alignment with source systems and contractual logic.
  • Continuously optimize data models and warehouse performance to support large scale claims volumes and time-sensitive financial analysis.
  • Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability.
  • Communicate complex financial insights clearly through data memos, documentation and presentations for both technical and non technical stakeholders.
  • Explore advanced analytics and predictive modeling use cases (e.g utilization forecasting, trend analysis, risk stratification, margin sensitivity) to enhance financial planning and decision making. Experience operationalizing ML models is a plus.

WHO YOU ARE:

  • Expert level proficiency in SQL and statistical programming (Python, R).
  • 3 to 4 years working experience with data modeling, dbt and analytics engineering best practices (testing, documentation, incremental models, semantic layers).
  • Experience in cloud platforms (preferably in AWS) and hands-on experience in cloud data warehouses (Redshift or Snowflake).
  • Business acumen with exposure to PBM, healthcare finance, underwriting or actuarial concepts.
  • Experience modeling large scale claims data and translating contractual or financial rules into clear, testable data logic.
  • Strong analytical and problem-solving skills.
  • Ability to understand, tackle, and solve problems from both technical and business perspectives.
  • Comfortable partnering closely with finance, underwriting and operations stakeholders to align data models with real world financial decisions.
  • High attention to detail and a bias toward accuracy, transparency and explainability in financial reporting.

COMPENSATION:  $140,000 annually, in addition to bonus and equity

Compensation offered will be determined by geographic location, experience, and qualifications.