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Data Science Engineer Jobs in Colorado (NOW HIRING)

Senior Data Scientist (1), Data Analyst II (2), Data Engineer (3). Minimum education and experience required: Master's degree or the equivalent in Computer Science, Engineering, Data Science or ...

We are seeking a Data Scientist to support our NLP project focused on accurate and automatic ... Computer Science or a degree in a related field (Computer Information Systems, Engineering), a ...

This role sits at the intersection of data engineering, data science, and machine learning, with a specific focus on acoustic and sensor data. You will be instrumental in designing, developing, and ...

Required : • PhD or MSc in a quantitative field such as Computer Science, Statistics, or Engineering, or equivalent industry experience delivering complex data science projects. • Demonstrable ...

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Data Science Engineer information

See Colorado salary details

$46.8K

$136.4K

$186.6K

How much do data science engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for data science engineer in Colorado is $136,399.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,400.00 and $144,600.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What are the most commonly searched types of Data Science Engineer jobs in Colorado? The most popular types of Data Science Engineer jobs in Colorado are:
What are popular job titles related to Data Science Engineer jobs in Colorado? For Data Science Engineer jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Data Science Engineer jobs? Cities in Colorado with the most Data Science Engineer job openings:
Manager, Data Engineering

Manager, Data Engineering

Walmart

Denver, CO • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 18 days ago


Walmart rating

6.0

Company rating: 6.0 out of 10

Based on 21,648 frontline employees who took The Breakroom Quiz

22nd of 39 rated national retailers


Job description

This notice is being provided as a result of the filing of an Application for Permanent Alien Labor Certification. Any person may provide documentary evidence bearing on the application to the Certifying Officer of the Department of Labor: U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210What you'll do...

Position: Manager, Data Engineering

Job Location: 55 Madison Street, Suite 800, Denver, CO 80206

Duties: Tech Problem Formulation Requires knowledge of: Analytics/big data analytics / automation techniques and methods; Business understanding; Precedence and use cases; Business requirements and insights. To translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Understanding Business Context Requires knowledge of: Industry and environmental factors; Common business vernacular; Business practices across two or more domains such as product, finance, marketing, sales, technology, business systems, and human resources and in-depth knowledge of related practices; Directly relevant business metrics and business areas. To provide recommendations to business stakeholders to solve complex business issues. Develops business cases for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities. Data Source Identification Requires knowledge of: Functional business domain and scenarios; Categories of data and where it is held; Business data requirements; Database technologies and distributed datastores (e.g. SQL, NoSQL); Data Quality; Existing business systems and processes, including the key drivers and measures of success. To support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data. Data Transformation and Integration Requires knowledge of: Internal and external data sources including how they are collected, where and how they are stored, and interrelationships, both within and external to the organization; Techniques like ETL batch processing, streaming ingestion, scrapers, API and crawlers; Data warehousing service for structured and semi-structured data, or to MPP databases such as Snowflake, Microsoft Azure, Presto or Google BigQuery; Pre-processing techniques such as transformation, integration, normalization, feature extraction, to identify and apply appropriate methods; Techniques such as decision trees, advanced regression techniques such as LASSO methods, random forests etc; Cloud and big data environments like EDO2 systems. To extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends. This position supervises six employees: Senior Data Scientist (1), Data Analyst II (2), Data Engineer (3).

Minimum education and experience required: Master's degree or the equivalent in Computer Science, Engineering, Data Science or related field and 1 year of experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field; OR Bachelor's degree or the equivalent in Computer Science, Engineering, Data Science or related field and 3 years of experience in software engineering, data engineering, database engineering, business intelligence, business analytics or related field.

Skills required: Experience in the design and development of Extract, Transform, Load (ETL) pipelines to move data from source systems to data warehouses and lakes. Experience with database technologies such as Cassandra, MongoDB, MySQL, PostgreSQL, Redis and cloud data warehouses such as Snowflake, Google Big Query and Redshift. Experience in programming languages like Python (PySpark) for data manipulation and pipeline automation at scale. Experience in creating interactive dashboards and reports using BI tools like Tableau, Power BI and ThoughtSpot. Experience with statistical analysis and tools like R and Python (Pandas and NumPy). Experience with SQL skills for querying large datasets and ensuring data quality. Experience with best practices in data privacy and governance. Experience with cloud platforms such as AWS, Microsoft Azure and Google Cloud Platform for big data storage, computer services, and data pipeline orchestration. Experience with various revenue sources including impression data from ad tech and revenue systems. Experience developing, maintaining, and optimizing data pipelines using modern tech stack (Databricks, Snowflake, and Apache Airflow). Expertise in television, soundbar and user data collected from various sources (Internet of Things (IoT), software, and external sources). Employer will accept any amount of experience with the required skills.

Salary Range: $167,336/year to $242,000/year. Additional compensation includes annual or quarterly performance incentives.

Benefits: At Walmart, we offer competitive pay as well as performance-based incentive awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty and voting. Other benefits include short-term and long-term disability, education assistance with 100% company paid college degrees, company discounts, military service pay, adoption expense reimbursement, and more.

Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms. For information about benefits and eligibility, see One.Walmart.com.

Wal-Mart is an Equal Opportunity Employer.

#LI-DNI #LI-DNP

Pay Rate...$0.00Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.

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About Walmart

Sourced by ZipRecruiter

From our humble beginnings as a small discount retailer in Rogers, Ark., Walmart has opened thousands of stores in the U.S. and expanded internationally. Through innovation, we're creating a seamless experience to let customers shop anytime and anywhere online and in stores. We are creating opportunities and bringing value to customers and communities around the globe. Walmart operates approximately 10,500 stores and clubs in 19 countries and eCommerce websites. We employ 2.1 million associates around the world — nearly 1.6 million in the U.S. alone.

Industry

Retail and transportation and warehousing

Company size

10,000+ Employees

Headquarters location

Bentonville, AR, US

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