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Senior Data Analytics Engineer Jobs (NOW HIRING)

Data & Analytics Engineer

Milwaukee, WI · On-site

$112K - $135K/yr

Implement and test end-to-end data solutions under the guidance of senior engineers * Follow established practices to ensure sensitive data is protected and handled appropriately Analytics Enablement ...

C) Analytics engineering: data products, semantic layer, and standardized metrics * Design and own curated analytics datasets and reusable dimensional models that become a "single source of truth ...

Senior Data Analytics Engineer

San Francisco, CA · On-site

$124K - $169K/yr

They are seeking their first data analytics hire to establish and own the data foundation for their ... Hyperbolic is the open-access AI cloud made for AI developers, providing fast, affordable access to ...

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 ...

Data Analytics Engineer

Glen Allen, VA · On-site

$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 ...

Data Analytics Engineer

Houston, TX · On-site

$99K - $118K/yr

Data Analytics Engineer Location: Houston TX (4 days in office) Type: Full Time This role is a ... You'll work closely with the Sr. Manager, Data & Analytics, and with business stakeholders across ...

Senior Data and Analytics Developer Full Time Perm Salary: $96,600 - $144,900, plus 8% annual bonus Way of Work: Hybrid - 3 days on location Location: Columbus, OH Relocation assistance provided ...

Data Analytics Engineer

Austin, TX · On-site

$108K - $129K/yr

The Data Analytics Engineer is responsible for designing, building, and maintaining scalable data pipelines, analytics platforms, and reporting solutions that enable data-driven decision making ...

Showing results 21-40

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 Sep 2, 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 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.

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 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.

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.

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Infographic showing various Senior Data Analytics Engineer job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $126,328 per year, or $60.7 per hour.

Data & Analytics Engineer

Baird

Milwaukee, WI • On-site

$112K - $135K/yr

Full-time

Re-posted 25 days ago


Baird rating

8.5

Company rating: 8.5 out of 10

Based on 11 frontline employees who took The Breakroom Quiz


Job description

About the Role:
Are you energized by transforming complex financial services data into meaningful insights that influence real business decisions? Do you enjoy blending hands-on technical work with close collaboration across business teams? Are you looking for an opportunity to expand your expertise in analytics engineering, data modeling, and modern cloud data platforms in an environment that values curiosity and continuous learning?
As Baird continues to invest in data as a strategic asset, we are adding a Data & Analytics Engineer to our growing IT Data Team. In this role, you'll play a meaningful part in shaping how financial services data is structured, transformed, and delivered to drive smarter decision-making across the firm. You'll contribute to building scalable, high-quality data solutions while partnering closely with stakeholders to turn evolving business needs into actionable insights.
This is an excellent opportunity for a data professional who thrives in a collaborative, agile environment and enjoys solving complex problems while delivering incremental value. You'll gain exposure to modern data tools and practices, work alongside experienced engineers and architects, and continuously grow your technical and business acumen.
This position is hybrid, offering a combination of 2 day/week remote work and 3 days/week in our collaborative downtown Milwaukee workspace. At Baird, you'll find a supportive culture centered on teamwork, continuous learning, and making a meaningful impact through data.
The Impact You'll Make:
Data Engineering & Data Management:
  • Contribute to the design, build, and maintenance of data pipelines that ingest and transform financial services data
  • Apply data modeling skills (3NF and dimensional) to support analytics-ready datasets
  • Perform data analysis and profiling to understand source data and support quality outcomes
  • Develop and validate source-to-target mappings and transformation logic
  • Implement and test end-to-end data solutions under the guidance of senior engineers
  • Follow established practices to ensure sensitive data is protected and handled appropriately

Analytics Enablement & Delivery:
  • Support data discovery efforts and help prototype datasets that bring together multiple data sources
  • Leverage existing tools to enable reporting and visualization for financial services users
  • Document datasets and transformations to support usability and adoption
  • Deliver work incrementally while balancing changing priorities

Collaboration, Learning & Growth:
  • Collaborate with delivery team members, architects, and business partners
  • Communicate clearly about progress, risks, and dependencies
  • Learn and apply Baird data standards, tools, and best practices
  • Seek feedback and coaching from senior Data & Analytics Engineers
  • Continuously build skills through training, documentation, and hands-on experience

What You'll Bring to Baird:
  • 5-7 years of experience delivering data and analytics solutions in a collaborative environment
  • Experience in data engineering, analytics engineering, business intelligence development, or a related data-focused role
  • Strong SQL skills and familiarity with relational database concepts and best practices
  • Experience performing data analysis, profiling, validation, and troubleshooting to support reliable data solutions
  • Ability to partner effectively with business stakeholders to understand requirements and support analytics needs
  • Strong problem-solving skills, intellectual curiosity, and a desire to continuously grow technical expertise
  • Experience with databases and platforms such as SQL Server, Snowflake, Azure SQL Database, and Azure Data Lake
  • Experience writing queries and developing solutions using SQL, T-SQL, Azure Data Studio, or similar tools
  • Familiarity with BI and analytics tools such as Power BI, Alteryx, or comparable platforms
  • Working knowledge of data modeling and governance concepts, including 3NF, dimensional modeling, data mapping, data profiling, and data quality practices
  • Experience working with common data formats such as CSV, JSON, XML, and Parquet
  • Experience working in a regulated or data-sensitive environment is preferred
  • Bachelor's degree in Computer Science, MIS, Business Administration, Finance, or equivalent experience

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