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Senior Data Analytics Engineer Jobs (NOW HIRING)

Propelus

Senior Data Analytics Engineer

$100K - $140K/yr

As an Analytics Engineer, you will play a crucial role in transforming raw data into actionable insights to support data-driven decision-making across the company. You will work independently on ...

KORE1 Technologies

Data Analytics Engineer

Glen Allen, VA

$106K - $127K/yr

... hiring a Data Analytics Engineer to help build the data foundation that powers trustworthy ... This is a senior individual contributor role. You'll lead through technical ownership, influence ...

AmaWaterways, LLC

Data Analytics Engineer

Calabasas, CA · On-site

$90K - $100K/yr

Partner with the Senior Data Engineer to make sure the source pipelines you depend on are designed ... AI-native analytics engineering * Use Claude Code as your primary working environment, including ...

KORE1 Technologies

Data Analytics Engineer

Glen Allen, VA · On-site

$180K - $200K/yr

... hiring a Data Analytics Engineer to help build the data foundation that powers trustworthy ... This is a senior individual contributor role. You'll lead through technical ownership, influence ...

StandardAero

Sr. Data Analytics Developer

Dallas, TX · On-site

As a Senior Data Analytics Developer, you have deep experience in data analysis, data transformation, data modelling and Power BI report/ dashboard development. Using this skillset, you will work ...

PTMA Financial Solutions

Data Analytics Engineer

Denver, CO · On-site

$117K - $141K/yr

The Data Analytics Engineer is responsible for delivering business-facing analytics in a regulated ... senior team members. • Define, document, and govern enterprise KPIs (e.g., AUM, cash flows ...

TAB Bank

Data Analytics Engineer

Ogden, UT · On-site

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bank's Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering ...

TAB Bank

Data Analytics Engineer

Ogden, UT

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bank's Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering ...

TAB Bank

Data Analytics Engineer

Ogden, UT · On-site

$112K - $134K/yr

Data Analyst Engineer to design, develop, and maintain scalable data solutions that support the bank's Business Intelligence pipelines, modeling, and reporting. This role bridges data engineering ...

Skanska USA

Data Analytics Engineer

Durham, NC

$110K - $132K/yr

The Data Analytics Engineer plays a crucial role in designing, implementing, and supporting enterprise data initiatives and analyses. The Data Analytics Engineer focuses on creating intuitive data ...

Request Technology, LLC

Data Analytics Engineer

Chicago, IL · Hybrid

$118K - $141K/yr

Continuously expand knowledge of data and analytics engineering methodologies to enhance infrastructure maintainability and reliability * Champion self-service capabilities and data literacy among ...

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Senior Data Analytics Engineer information

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$81K

$126.3K

$175K

How much do senior data analytics engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for senior data analytics engineer in the United States is $126,328.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,000.00 and $144,000.00 per year, depending on experience, location, and employer.

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

AspectSenior Data Analytics EngineerData Scientist
CredentialsBachelor's/Master's in Data Science, Computer Science, or related fieldsBachelor's/Master's in Data Science, Statistics, or related fields
Work EnvironmentFocus on data pipelines, analytics tools, and reporting systemsFocus on model development, statistical analysis, and predictive modeling
Industry UsageUsed in analytics teams to build data infrastructure and insightsUsed in R&D, product development, and research teams for modeling

While both roles require strong analytical skills and similar educational backgrounds, Senior Data Analytics Engineers primarily focus on building and maintaining data infrastructure and delivering insights through analytics tools. Data Scientists, on the other hand, concentrate on developing predictive models and statistical analysis. The roles often collaborate but serve different functions within data-driven organizations.

How does a Senior Data Analytics Engineer typically collaborate with cross-functional teams to deliver insights?

As a Senior Data Analytics Engineer, you will frequently work with stakeholders in product, marketing, and engineering to translate business needs into data solutions. This involves gathering requirements, designing and building data pipelines, and presenting actionable insights. Effective communication and regular meetings with team members ensure that data models and dashboards align with business objectives. You may also mentor junior analysts and engineers, fostering a collaborative and knowledge-sharing environment.

What does a Senior Data Analytics Engineer do?

A Senior Data Analytics Engineer is responsible for designing, developing, and maintaining scalable data pipelines and analytical solutions. They work closely with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability. Their role often includes optimizing data workflows, implementing best practices in data management, and mentoring junior team members. Additionally, they help translate business needs into technical solutions to support data-driven decision making.

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

To thrive as a Senior Data Analytics Engineer, you need expertise in statistics, data modeling, and programming languages such as Python or SQL, typically backed by a degree in computer science, engineering, or a related field. Experience with data analytics tools (e.g., Tableau, Power BI), cloud platforms (e.g., AWS, Azure), and relevant certifications like Google Data Engineer are highly valued. Strong problem-solving, communication, and leadership skills help you translate complex data insights into actionable business strategies and mentor junior team members. These capabilities are crucial for delivering accurate data-driven solutions that drive organizational decision-making and innovation.
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What cities are hiring for Senior Data Analytics Engineer jobs? Cities with the most Senior Data Analytics Engineer job openings:
What are the most commonly searched types of Data Analytics Engineer jobs? The most popular types of Data Analytics Engineer jobs are:
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Senior Data Analytics Engineer jobs near you
Infographic showing various Senior Data Analytics Engineer job openings in the United States as of May 2026, with employment types broken down into 79% Full Time, 13% Part Time, and 8% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $126,328 per year, or $60.7 per hour.

Senior Data Analytics Engineer

Propelus

Remote

$100K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago

Job description

Propelus® simplifies workforce compliance management across healthcare. Our innovative technology and strategic partnerships empower millions of professionals, their employers, and regulators to work together, creating a connected and efficient healthcare ecosystem.
As a trusted leader for over 20 years, Propelus has focused on bringing more good into the lives of the people and organizations serving healthcare. We deliver seamless compliance solutions to millions. We leverage market-leading technology and essential data to simplify complex operations, reduce risk, and champion a safer, healthier, and happier workforce.
Job Summary: As an Analytics Engineer, you will play a crucial role in transforming raw data into actionable insights to support data-driven decision-making across the company. You will work independently on assigned projects, collaborating with data scientists, product managers, and engineers to build, maintain, and improve our data infrastructure and analytics pipelines. Your work will contribute directly to the efficiency and effectiveness of our compliance management technology, enabling us to better serve our clients and drive innovation. You will contribute to the delivery of key datasets and reports, ensuring data quality and accessibility.
Key Responsibilities include, but are not limited to:
  1. Develop and maintain robust and scalable data pipelines to extract, transform, and load (ETL) data from various sources into our data warehouse.
  2. Design, build, and optimize data models to support analytical needs and reporting requirements.
  3. Collaborate with data scientists to implement and deploy machine learning models and analytical solutions.
  4. Monitor data quality and identify and resolve data integrity issues.
  5. Contribute to the development of data documentation and metadata management practices.
  6. Work with stakeholders to understand their data needs and translate them into technical requirements.
  7. Assist in the evaluation and implementation of new data technologies and tools.
  8. Participate in code reviews and contribute to the development of coding standards and best practices.
  9. Independently manage assigned tasks and projects, ensuring timely delivery and quality results.
  10. Proactively identify opportunities to improve data processes and systems.

Qualifications & Desired Skills:
  1. Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
  2. 4+ years of experience in data engineering, analytics engineering, or a similar role.
  3. Proficiency in SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
  4. Familiarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and related data warehousing services (e.g., Snowflake, Redshift, BigQuery).
  5. Familiarity with data testing frameworks.
  6. Experience with ETL tools and techniques (e.g., Apache Airflow, dbt).
  7. Solid understanding of data modeling principles and data warehouse architecture.
  8. Strong analytical and problem-solving skills.
  9. Experience with at least one programming language (e.g., Python, Java).
  10. Good communication and collaboration skills.
  11. Proficiency in using Git for version control and collaboration on codebase.

Benefits and Perks for Propelus employees include but are not limited to:
  • Awarded one of BuiltIn's 2025 Best Places to Work and honored as a Silver Stevie® Award Winner in the 2025 Stevie Awards For Great Employers.
  • Professional development allowance to help you grow in the ways that mean the most to you.
  • Flexibility for balancing work with the rest of life and ample PTO, including paid time off for volunteering, your birthday, and becoming a new parent.
  • Check us out for yourself at our careers page or our Propelus culture Instagram accounts.

For US Employees:
  • 401K with company matching, as well as financial planning education and resources.
  • Employees can choose from HSA, FSA, and traditional insurance options for medical, dental, and vision coverage for themselves and dependents.
  • Lifestyle Spending Account (LSA): We support personal well-being by offering an annual lifestyle spending account that you can use for what matters most to you-whether it's a gym membership, a meditation app, WFH equipment, or fresh produce delivered to your door.

For LATAM Employees:
  • Your health is our top priority! We cover 100% of your health insurance premiums. Our plans include national and international coverage, so you're protected no matter where you are.
  • Propelus Flex Club: Our flexible benefits platform gives you monthly points to redeem on what you need most. Plus, you'll get access to exclusive discounts just for being part of our team.
  • We've got you covered with a life insurance policy, paid 100% by the company. You can also add your beneficiaries at an exclusive, discounted rate.

We are an equal opportunity employer and value diversity at Propelus. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Candidates from all backgrounds are encouraged to apply.
Full-time positions are scheduled to work 40 hours per week, M-F unless required otherwise by projects. Part-time positions are scheduled to work a maximum of 30 hours per week. Equipment, benefits, and perks are not provided to part-time or temporary employees.

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