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Entry Level Startup Data Engineer Jobs (NOW HIRING)

Data Engineer I

Farmers Branch, TX

$110K - $132K/yr

The Data Engineer I (DE I) is an entry-level engineering position responsible for contributing to the development of the enterprise data platform. This role applies foundational data engineering ...

Data Engineer I

Gainesville, FL · On-site

$65K - $78K/yr

UF Information Technology (UFIT) is currently seeking an entry-level Data Engineer I to join Data Platform and Analytics - Data Engineering, a unit within UFIT. UF Information Technology (UFIT ...

Mid-Level Data Engineer

$117K - $140K/yr

MDAEdge is a company focused on data engineering solutions, and they are seeking a Mid-Level Data ... in startup environments is a plus Company : The world doesn't have a talent shortage. It has a ...

Data Engineer

Huntsville, AL · On-site

$60K - $83K/yr

Responsibilities We are seeking an entry-level Data Engineer to join our practice with a dedicated focus on military clients in the Defense & Security segment. You will collaborate with cross ...

Data Engineer

Huntsville, AL

$106K - $128K/yr

Responsibilities We are seeking an entry-level Data Engineer to join our practice with a dedicated focus on military clients in the Defense & Security segment. You will collaborate with cross ...

Data Engineer

Huntsville, AL · On-site

$106K - $128K/yr

Responsibilities We are seeking an entry-level Data Engineer to join our practice with a dedicated focus on military clients in the Defense & Security segment. You will collaborate with cross ...

Data Engineer, Palo Alto

Palo Alto, CA · On-site

$110K - $180K/yr

Our Data Engineers work cross functionally with other departments to meet business needs. They ... startup located in the heart of Silicon Valley at Stanford Research Park in Palo Alto. We use ...

Entry level Data Engineer - New Grad

Austin, TX · Hybrid

$113K - $136K/yr

As an Entry Level Data Engineer, you'll help build and support the data pipelines, integrations, and automated workflows that power our eCommerce, inventory, fulfillment, analytics, and customer ...

Data Engineer, Palo Alto

Palo Alto, CA · On-site

$110K - $180K/yr

Our Data Engineers work cross functionally with other departments to meet business needs. They ... startup located in the heart of Silicon Valley at Stanford Research Park in Palo Alto. We use ...

Data Engineer

Somerville, MA · On-site

$125K - $150K/yr

Position Overview Matterworks is seeking a Data Engineer to build and run the pipelines behind our ... A passion for contributing to an early-stage startup where autonomy, eagerness to learn, and ...

Entry level Data Engineer - New Grad

Austin, TX · Hybrid

$113K - $136K/yr

As an Entry Level Data Engineer, you'll help build and support the data pipelines, integrations, and automated workflows that power our eCommerce, inventory, fulfillment, analytics, and customer ...

Data Engineer

Atlanta, GA · On-site

$110K - $132K/yr

Our Newest Opportunity: We're building a modern, AI-native data engineering function on Azure ... Experience: 2+ years preferred; Entry Level Candidates with strong projects encouraged to apply ...

Data Engineer II , GTMO DATA

Seattle, WA · On-site

$130K - $156K/yr

At Amazon Business, a fast-growing startup passionate about building solutions, we set out every ... Amazon Business Team is looking for a Data Engineer (DE) to play a significant role in building a ...

AI Data Engineer

Provo, UT · On-site

$109K - $131K/yr

AI Data Engineer Customer Experience | Provo, UT | Full-Time | On-Site | $50,000 - $90,000 | Entry-Level / 0-2 Years ABOUT ATONOM Atonom.ai builds Cloud Employees: intelligent AI agents that execute ...

Data Engineer (Contract) (Remote)

Manhattan, NY · Remote

$126K - $151K/yr

We are seeking a skilled Data Engineer to join our dynamic team. This role involves developing and ... Previous consulting or startup environment experience. * Ability to independently handle customer ...

Showing results 21-40

Entry Level Startup Data Engineer information

See salary details

$44.5K

$129.7K

$177.5K

How much do entry level startup data engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for entry level startup data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What does an entry level startup data engineer do?

An Entry Level Startup Data Engineer is responsible for building and maintaining the data infrastructure that supports a startup's analytics and business operations. They typically work with databases, data pipelines, and cloud platforms to collect, process, and store data from various sources. Their tasks often include cleaning and transforming raw data, ensuring data quality, and assisting data analysts or scientists by providing them with reliable datasets. Because startups often have smaller teams, entry-level data engineers may also take on a variety of technical tasks and collaborate closely with software engineers and product managers. This role is ideal for those looking to gain broad experience in data engineering within a fast-paced, innovative environment.

What are the key skills and qualifications needed to thrive as an entry level startup data engineer, and why are they important?

To thrive as an Entry Level Startup Data Engineer, you need a solid understanding of programming languages like Python or SQL, data modeling, and a relevant degree such as computer science or engineering. Familiarity with data pipelines, cloud platforms (e.g., AWS, Google Cloud), and tools like Apache Spark or ETL systems is typically required. Strong problem-solving abilities, adaptability, and effective communication skills help you excel in a fast-paced, evolving environment. These competencies are crucial for building reliable data solutions and collaborating well within lean startup teams.

What are some common challenges faced by entry level startup data engineers, and how can they be addressed?

Entry level data engineers at startups often encounter challenges such as working with rapidly evolving tech stacks, limited documentation, and balancing multiple responsibilities due to smaller teams. Adapting quickly and proactively seeking clarification from team members is key. Building strong communication with software engineers, data scientists, and product managers helps ensure alignment on data requirements and project priorities. Taking initiative to document solutions and automate repetitive tasks can also improve efficiency and contribute to team success.

What is the difference between Entry Level Startup Data Engineer vs Data Analyst?

AspectEntry Level Startup Data EngineerData Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; basic SQL, Python, or Spark knowledgeBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and visualization tools
Work EnvironmentStartups, fast-paced, collaborative, technical focus on data pipelines and infrastructureVarious industries, focus on data interpretation, reporting, and business insights
Employer & Industry UsageTech startups, SaaS companies, e-commerceFinance, marketing, healthcare, retail

Entry Level Startup Data Engineers focus on building data infrastructure and pipelines, requiring technical skills like SQL and Python. Data Analysts interpret data to generate insights, often using visualization tools. While both roles work with data, engineers develop the systems, and analysts analyze data for decision-making.

More about Entry Level Startup Data Engineer jobs

What cities are hiring for Entry Level Startup Data Engineer jobs?

Cities with the most Entry Level Startup Data Engineer job openings:

What are the most commonly searched types of Startup Data Engineer jobs?

The most popular types of Startup Data Engineer jobs are:

What states have the most Entry Level Startup Data Engineer jobs?

States with the most job openings for Entry Level Startup Data Engineer jobs include:

Infographic showing various Entry Level Startup Data 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 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

$110K - $132K/yr

Full-time

Medical, Life, Retirement

Posted 16 days ago


Job description

JOIN THE BEST TEAM IN SPORT & SPIRIT

At Varsity Brands, we believe every student deserves the opportunity to succeed and every educator wants to make a difference. It takes a team to make a real impact, and through our two divisions - BSN SPORTS and Varsity Spirit - and our network of 6,000+ employees and independent representatives, we are proud to partner with a wide range of educational institutions and club and professional sports to transform the student journey in SPORT and SPIRIT.

LOCATION: 14460 Varsity Brands Way Farmers Branch, Tx - Varsity Brands HQ

WORK TYPE: Onsite

HOW YOU WILL MAKE AN IMPACT:

Varsity Brands is building a modern enterprise data platform that powers analytics, reporting, artificial intelligence, and data-driven decision-making across the organization. The platform brings together data from enterprise applications, digital products, manufacturing, supply chain, and customer systems into trusted, scalable, and governed data products and platform capabilities that enable analytics, operational intelligence, and AI.

The Data Engineer I (DE I) is an entry-level engineering position responsible for contributing to the development of the enterprise data platform. This role applies foundational data engineering knowledge and exercises independent judgment in executing assigned work, including selecting appropriate approaches within established engineering standards to develop, test, and maintain data pipelines, transformations, and data products.

This role is designed to develop the next generation of data engineers who will help build the trusted data foundation supporting Varsity Brands' analytics, operational intelligence, and AI strategy.

Impact of the Role

  • Contributes to delivery of trusted data pipelines and data products supporting analytics, reporting, and AI initiatives
  • Builds foundational engineering capabilities supporting a scalable, cloud-based enterprise data platform
  • Improves data accessibility, consistency, and quality across enterprise systems
  • Supports the organization's transition from fragmented data sources to governed, reusable enterprise data assets

WHAT YOU WILL DO:

  • Develop, test, and maintain data pipelines, transformations, and data integration processes using established engineering standards
  • Assist in building and maintaining data products that support analytics, reporting, and AI use cases
  • Write, optimize, and troubleshoot SQL queries and data transformations
  • Participate in code reviews and incorporate feedback to improve quality, maintainability, and performance
  • Troubleshoot lower-complexity data pipeline and data quality issues, exercising sound judgment to identify appropriate solutions and escalating when necessary
  • Collaborate with Data Engineering, Analytics Engineering, Business Intelligence, Enterprise Architecture, Application Engineering, and business stakeholders to deliver reliable data solutions
  • Follow established engineering practices for testing, version control, CI/CD, security, and documentation
  • Contribute to data quality, observability, and monitoring activities to improve platform reliability
  • Document data pipelines, transformation logic, metadata, and engineering processes to support knowledge sharing and operational continuity
  • Develop working knowledge of enterprise data architecture, cloud data platforms, orchestration frameworks, and engineering patterns to support future growth into independent ownership

Key Performance Indicators

Success in this role will be measured through:

  • Quality and reliability of delivered data pipelines and transformations
  • Timely completion of assigned engineering work
  • Accuracy and quality of data supporting downstream consumers
  • Ability to troubleshoot and resolve issues with increasing independence
  • Consistent adoption of engineering standards, documentation, and development practices
  • Demonstrated growth in technical capability and understanding of the enterprise data platform

QUALIFICATIONS:

Knowledge, Skills, Abilities

The ideal candidate will demonstrate the following capabilities:

Technical Knowledge

  • Foundational understanding of data engineering principles and modern data platforms
  • Basic Understanding of relational databases, data modeling, and data integration concepts
  • Familiarity with cloud-based data platforms and modern data engineering environments
  • Basic understanding of data governance, data quality, and metadata concepts

Technical Skills

  • Ability to develop and test SQL queries and data transformations
  • Foundational programming skills using Python or a comparable language
  • Familiarity with modern data engineering tools and technologies, including:
    • Modern cloud data platforms (Snowflake preferred)
    • SQL
    • Python for data engineering and automation
    • Git-based version control
    • ETL/ELT concepts
  • Basic understanding of CI/CD and automated testing concepts

Cognitive & Problem-Solving Abilities

  • Applies logical reasoning to solve defined technical problems
  • Exercises independent judgment in selecting approaches within established engineering guidelines
  • Identifies data quality and pipeline issues and escalates appropriately when needed
  • Demonstrates attention to detail and commitment to producing accurate, reliable data

Collaboration & Communication

  • Communicates effectively within cross-functional team environments
  • Collaborates with engineers, analysts, architects, and business stakeholders
  • Actively participates in team discussions and engineering ceremonies
  • Incorporates coaching and feedback to improve technical capability

Learning Agility

  • Demonstrates curiosity and willingness to learn emerging data technologies and engineering practices
  • Adapts to evolving cloud platforms, tools, and business priorities
  • Builds understanding of enterprise data architecture and modern data engineering patterns

Continuous Improvement

  • Identifies opportunities to automate, simplify, and improve engineering processes
  • Seeks opportunities to reduce technical debt and improve operational excellence

Education, Certification and Experience

Ideal candidates will bring the following experience and capabilities:

Required

  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, or a related technical discipline; or equivalent combination of education and experience
  • 0 - 2 years of relevant experience, including internships, academic projects, or early career experience in data engineering, software engineering, analytics engineering, or related technical disciplines
  • Foundational knowledge of SQL and relational databases

Preferred

  • Exposure to cloud data platforms such as Snowflake
  • Exposure to Python, dbt, or comparable data transformation tools
  • Familiarity with Git, CI/CD, and Agile software development practices
  • Experience working with modern data visualization or analytics platforms through coursework, internships, or projects

Physical Demands and/or Work Environment

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

#LI_JF


Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job.


OUR VALUES

Service - We lead with heart. We champion community.

Passion - We love what we do. It fuels our purpose.

Integrity - We do what we promise. We own our actions and decisions.

Respect - We earn it by giving it. Because everyone deserves it.

Innovation - We never stop striving to be better. For ourselves and our community.

Transparency - We are committed to openness and honesty in everything we do.


OUR BENEFITS

We are committed to putting you and your families first. For benefits eligible roles, we offer a variety of choices and costs as well as program enhancements that align with our responsibility to elevate the employee experience. Some of our offerings include:

  • Comprehensive Health Care Benefits
  • HSA Employer Contribution/ FSA Opportunities
  • Wellbeing Program
  • 401(k) plan with company matching
  • Company paid Life, AD&D, and Short-Term Disability
  • Generous My Time Off & Paid Holidays
  • Varsity Brands Ownership Program
  • Employee Resource Groups
  • Access to Financial Coaching and member-owned Credit Union
  • St. Jude Partnership & Volunteer Opportunities
  • Employee Perks including discounts on personal apparel and equipment!


Varsity Brands companies are equal opportunity employers. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, citizenship, gender, sexual orientation, gender identity, veteran's status, age or disability.