1

Data Software Engineer Jobs in Manhattan, KS (NOW HIRING)

Performs plan drafting using CAD software. * May work with engineering technician crews in testing, observations and data gathering activities on project sites and prepare daily reports documenting ...

Performs plan drafting using CAD software. * May work with engineering technician crews in testing, observations and data gathering activities on project sites and prepare daily reports documenting ...

May research and recommend network and data communications hardware and software. Position Description: * Establishes networking environment by designing system configuration; directing system ...

May research and recommend network and data communications hardware and software. Position Description: * Establishes networking environment by designing system configuration; directing system ...

Able to use basic computer software such as Word, Excel, and Outlook. * Use of computer based ... Pioneering engineered materials for more than 130 years, Michelin is uniquely positioned to make ...

next page

Showing results 1-20

Data Software Engineer information

See Manhattan, KS salary details

$39.4K

$114.9K

$157.2K

How much do data software engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for data software engineer in Manhattan, KS is $114,853.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,400.00 and $121,700.00 per year, depending on experience, location, and employer.

What engineers make $300,000 a year?

Senior software engineers, data engineers, and machine learning engineers with extensive experience, specialized skills, and often working in high-demand industries or companies can earn $300,000 or more annually. Achieving this level typically requires advanced technical expertise, certifications, and sometimes leadership responsibilities or stock options.

What engineers make $500,000?

Senior software engineers, especially those working in high-demand areas like technology, finance, or specialized fields such as machine learning or cybersecurity, can earn $500,000 or more annually. Achieving this level often requires extensive experience, advanced skills, and sometimes stock options or bonuses in addition to base salary.

What does a software data engineer do?

A software data engineer designs, builds, and maintains data pipelines and infrastructure to collect, process, and store large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible and reliable for analysis and decision-making. Strong programming skills and knowledge of database systems are essential for this role.

What are Data Software Engineers?

Data Software Engineers are professionals who design, build, and maintain the software systems that enable organizations to collect, process, and analyze large volumes of data. They bridge the gap between data engineering and software development by creating scalable, efficient pipelines and applications that support data-driven decision making. Their responsibilities often include developing data processing frameworks, ensuring data quality, and collaborating with data scientists and analysts to deliver actionable insights.

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

To thrive as a Data Software Engineer, you need strong programming skills (often in Python, Java, or Scala), a solid understanding of data structures and algorithms, and a background in computer science or a related field. Familiarity with big data frameworks (like Hadoop or Spark), database systems (SQL/NoSQL), and data pipeline tools is typically required, along with relevant certifications such as AWS Certified Data Analytics. Excellent problem-solving abilities, collaboration, and effective communication are soft skills that set top performers apart. These skills ensure the efficient design, development, and optimization of robust data systems critical for driving business insights and decision-making.

What is the difference between Data Software Engineer vs Data Engineer?

AspectData Software EngineerData Engineer
Primary FocusDeveloping software tools and applications for data processing and analysisBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsProgramming, software development, data modeling, often with certifications in software engineeringDatabase systems, ETL tools, cloud platforms, often with certifications in data engineering
Work EnvironmentSoftware development teams, data science teams, often in tech companiesData infrastructure teams, IT departments, cloud service providers

While both roles work with data, Data Software Engineers focus on creating software solutions for data analysis, whereas Data Engineers build the infrastructure to collect, store, and process data efficiently. Both roles require programming skills and often overlap, but their core responsibilities differ in scope and focus.

What are some common challenges Data Software Engineers face when working with large datasets?

Data Software Engineers often encounter challenges related to scalability, data quality, and system performance when handling large datasets. Ensuring that data pipelines can efficiently process high volumes of data without bottlenecks requires robust architecture and frequent optimization. Additionally, maintaining data integrity and consistency across distributed systems can be complex, especially when integrating data from multiple sources. Collaboration with data scientists, analysts, and DevOps teams is key to overcoming these challenges and building reliable, efficient data solutions.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their skills in programming, database management, and system architecture remain in high demand. AI tools serve as complements that enhance efficiency rather than substitutes for the core responsibilities of data engineers.
What are popular job titles related to Data Software Engineer jobs in Manhattan, KS? For Data Software Engineer jobs in Manhattan, KS, the most frequently searched job titles are:
Infographic showing various Data Software Engineer job openings in Manhattan, KS as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $114,853 per year, or $55.2 per hour.

Senior Data Platform Engineer

Purple Wave, Inc.

Manhattan, KS • On-site

$104K - $137K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago


Job description

Build the Data Platform That Powers What's Next.

We're seeking a seasoned Senior Data Platform Engineer to design and operate the pipelines, services, and data products that the rest of the company builds on. In this role, you'll own the flow of data end to end - ingesting and transforming it through ETL/ELT and dbt, orchestrating reliable batch and streaming workflows, and exposing it through the APIs and microservices that product teams depend on, including the next generation of features powered by large language models (LLMs) and machine learning. Beyond hands-on engineering, you'll shape technical direction, mentor teammates, and help drive standardization across the department. If you're energized by building dependable data systems and excited to apply LLMs and ML to real product problems, we'd love to have you on the team.

We are seeking an experienced Senior Data Platform Engineer to join our data team in building and maintaining a robust data platform and the backend services around it, while providing technical guidance and mentorship. This role focuses on designing and shipping high-quality data pipelines and transformations - building and maintaining ETL/ELT and dbt workflows, orchestration, and data-quality and observability practices - alongside the Python microservices and APIs that serve data and integrate LLM and ML capabilities into production. You'll also contribute to technical direction at the team level and lead standardization efforts across the department, collaborating closely with product teams and stakeholders to deliver reliable, scalable, and well-documented data and backend systems.

Responsibilities:

  • Technical Collaboration

    • Contribute to technical direction and strategic planning at the team level.

    • Evaluate and recommend new technologies and approaches for backend and AI/ML evolution.

    • Provide technical guidance and code reviews for team members.

    • Provide technical guidance and support to product teams consuming backend services.

  • Data Pipelines, ETL & Transformation

    • Design, build, and maintain data pipelines and ETL/ELT workflows that ingest, move, and transform data across source systems, the warehouse, and downstream consumers.

    • Develop and maintain dbt models, tests, and documentation to support analytics, reporting, and product features.

    • Build and operate workflow orchestration for batch and streaming data (scheduling, dependency management, retries, and alerting).

    • Establish and enforce data quality, reliability, and observability practices across pipelines (monitoring, lineage, freshness, and validation).

    • Implement schema management, versioning, and migration patterns to evolve data models safely.

    • Optimize pipeline performance, cost, and scalability across the data platform.

  • Data Application Development & Maintenance

    • Design, develop, and maintain microservices in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.

    • Design and build APIs and services that integrate LLMs and ML models - including retrieval-augmented generation, embeddings, prompt orchestration, tool/function calling, and agentic workflows.

    • Develop self-service tools and APIs that enable product teams to independently leverage backend and AI capabilities.

    • Establish patterns for safely, reliably, and cost-effectively operating LLM- and ML-backed features in production (evaluation, observability, guardrails, fallbacks).

    • Build and maintain CI/CD pipelines and deployment automation.

    • Create and maintain technical documentation and standards repositories.

  • Team Collaboration & Process

    • Work within an Agile framework to prioritize and deliver backend improvements.

    • Collaborate with product teams and stakeholders to understand requirements and pain points.

    • Help foster a culture of continuous learning, improvement, and technical excellence.

    • Encourage adoption of consistent tooling and processes across development teams.

    • Contribute to cross-team initiatives to improve developer experience and backend consistency.

  • Undertake additional assigned duties as requested.

Supervisory Responsibilities:

  • None.

Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or a related field, OR 6+ years of professional software development experience in lieu of degree.

  • 5+ years of backend software development experience.

  • 2+ years of experience in technical leadership or mentoring roles.

  • Programming Languages: Expert proficiency in Python; familiarity with Go and/or TypeScript/JavaScript is a plus.

  • LLMs & Machine Learning: Practical experience integrating LLMs or ML models into production systems - including at least several of: prompt engineering, RAG, embeddings/vector search, tool/function calling, evaluation, and cost/latency optimization.

  • Databases: Advanced experience with MySQL, PostgreSQL, and Redis; familiarity with vector databases (e.g., pgvector, Pinecone, Weaviate) is a plus.

  • APIs: Proven experience designing, building, and operating RESTful APIs at scale.

  • CI/CD: Advanced pipeline design and implementation using industry best practices and tools.

  • Infrastructure: Experience with cloud providers (AWS, Azure, GCP); container orchestration experience (Kubernetes) is a plus.

  • Proven experience building and scaling backend services and APIs.

  • Deep understanding of microservice architecture patterns, distributed systems, and best practices.

  • Experience with observability tools and practices (monitoring, logging, tracing) - including for AI/ML workloads where applicable.

  • Strong ability to communicate complex technical concepts to diverse audiences.

  • Strong customer-focused mindset with emphasis on the developer and end-user experience.

  • Experience facilitating technical discussions and building consensus.

  • Demonstrated experience providing technical guidance.

  • Spanish speaking bi-lingual candidates are encouraged to apply.

  • Candidates may be requested to complete position specific skills assessments.

  • Applicants must be either a U.S. Citizen or eligible to work in the U.S.

  • Requires the ability to satisfactorily complete a background check.

Working Settings:

  • Full-time Salaried Exempt, not eligible for overtime.
  • Office hours are 8am-5pm, Monday through Friday, Central Time zone, additional hours may be required depending on priorities.
  • This position is remote work eligible within the United States. Please be aware: the first week of employment includes mandatory in-person training. Remote start arrangements are not available.
  • Also mandatory: One week a year of in-person training with the department.
  • Potential for 10% travel, should the need arise.
  • Prolonged periods sitting at a desk and working on a computer.
  • Must be able to lift up to 15 pounds at times.

Compensation:

  • The salary varies based on experience and qualifications, but typically ranges from $100,000 to $125,000 per year.
  • Monthly Bonus Program - determined by the Company's monthly revenue result and are paid on a "percent to plan" payout formula (90% = $300, 100% = $600, 110% = $900, 120% = $1,200).
  • Monthly phone stipend in accordance with the Company's cell phone policy, currently $120/month.
  • Health, Dental, and Vision insurance.
  • 401(k) plan with an employer match up to 4% starting the first day of employment.
  • Company-paid Life Insurance with options for supplemental coverage.
  • Fully paid Short-Term Disability provided by the Company.
  • 3 Weeks of PTO annually (details shared during onboarding).
  • Employee Stock Purchase Program (ESPP) - Eligible to purchase company stock at a discount after 90 days of employment, with enrollment opportunities each May and November.