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Knime Analytics Platform Jobs (NOW HIRING)

Data Platform Engineer

Glendora, NJ · On-site

$110K - $132K/yr

Hands-on experience with KNIME Analytics Platform. * Experience with semantic layer technologies (e.g., AtScale, dbt Semantic Layer). * Experience implementing AI-driven data quality, anomaly ...

Audit Practices Manager

Jersey City, NJ · On-site

$108K - $142K/yr

Experience with KNIME analytics platform, Datasnipper, and AI tools are beneficial but not required. Talents Needed for Success: * Knowledge of Excel functions and macros * Deep understanding of ...

Audit Practices Manager

Jersey City, NJ · On-site

$113K - $149K/yr

Experience with KNIME analytics platform, Datasnipper, and AI tools are beneficial but not required. Talents Needed for Success: * Knowledge of Excel functions and macros * Deep understanding of ...

We specialize in Tableau, Power BI, Sigma, Omni, Alteryx, KNIME, Power Platform, and Snowflake. Responsibilities * Deliver on project-based consulting engagements and help clients develop analytical ...

We specialize in Tableau, Power BI, Sigma, Omni, Alteryx, KNIME, Power Platform, and Snowflake. Responsibilities * Deliver on project-based consulting engagements and help clients develop analytical ...

Familiarity with data wrangling tools like KNIME, Alteryx, or similar platforms * Coding skills in Python for data manipulation and analysis * Excellent analytical and problem-solving abilities

SQL (Teradata preferred) Looker / Qlik/Tableau Data Analysis Data Quality BI Development Data ... KNIME SQL/PLSQL Qlik ThoughtSpot Tableau Google Suite Strong mathematical, statistical and/or ...

... 2026 KNIME Customer Excellence Partner of the Year * Preferred Partner in the Anthropic Claude ... Work with cross-functional teams (Platform, Analytics, Operations, Sales, Delivery, Finance, IT) to ...

... 2026 KNIME Customer Excellence Partner of the Year * Preferred Partner in the Anthropic Claude ... We partner with major cloud data platforms like Snowflake, AWS, Azure, GCP, Fivetran, and dbt to ...

We are seeking a Principal Consultant with deep experience in platforms such as Microsoft Copilot ... Our consulting services emphasize analytics and agentic activation, data visualization, data ...

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Knime Analytics Platform information

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How much do knime analytics platform jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for knime analytics platform in the United States is $37.37, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $49.52 per hour, depending on experience, location, and employer.

What is the KNIME analytics platform used for?

The KNIME Analytics Platform is used for data analysis, data mining, and machine learning. It provides a visual workflow interface that allows users to build, deploy, and manage data workflows without extensive programming knowledge.

What is KNIME Analytics Platform?

KNIME Analytics Platform is an open-source software for data analytics, reporting, and integration. It provides a graphical interface that enables users to create data workflows without needing to write code, though coding is supported for advanced tasks. KNIME supports a wide range of data sources and integrates with popular machine learning and data mining libraries. It is widely used for tasks like data preprocessing, statistical analysis, and predictive modeling. The platform is popular among data scientists, analysts, and researchers for its flexibility and extensibility.

What is the difference between Knime Analytics Platform vs Data Analyst?

AspectKnime Analytics PlatformData Analyst
Required CredentialsProficiency in data analytics tools, certifications in data science or analyticsBachelor's degree in statistics, data science, or related field; certifications are a plus
Work EnvironmentData science teams, analytics departments, often in tech or finance industriesBusiness units, reporting teams, across various industries
Employer & Industry UsageUsed for data integration, machine learning, and automation in analytics projectsAnalyzing data, creating reports, supporting decision-making processes

Knime Analytics Platform is a powerful tool for data scientists and analytics teams, focusing on data processing and machine learning. Data Analysts typically use a variety of tools, including Knime, to interpret data and generate insights. While both roles require analytical skills, Knime specialists focus on building workflows and automation, whereas Data Analysts focus on interpreting data and reporting.

Which company uses KNIME?

Many companies across various industries use KNIME Analytics Platform for data analytics, machine learning, and automation tasks. Organizations such as pharmaceutical firms, financial institutions, and technology companies implement KNIME to streamline data workflows and improve decision-making processes. As a data analyst or KNIME specialist, familiarity with the platform can be valuable in roles that require data integration and advanced analytics skills.

What are some common challenges faced when onboarding new team members to projects using KNIME Analytics Platform?

Onboarding new team members to projects in KNIME Analytics Platform often involves ensuring familiarity with KNIME's workflow-based interface and the specific extensions used in your organization. New users may initially find it challenging to adapt to KNIME’s node-based approach, especially if they are more accustomed to coding-centric data tools. Providing access to well-documented, modular workflows and encouraging participation in KNIME’s community forums can accelerate learning. Collaboration is typically enhanced through version control integrations and shared workspace environments, which help new members quickly align with team standards and best practices.

What are the key skills and qualifications needed to thrive as a KNIME Analytics Platform specialist, and why are they important?

To thrive as a KNIME Analytics Platform specialist, you need a solid background in data analysis, statistics, and experience with data integration and workflow automation. Familiarity with the KNIME software suite, data visualization tools, and scripting languages such as Python or R, as well as relevant certifications like KNIME Certified Analytics Professional, are highly beneficial. Strong problem-solving skills, attention to detail, and effective communication set top performers apart in this role. These skills and qualifications enable professionals to efficiently manage data-driven projects, deliver actionable insights, and support business decision-making.

How does KNIME compare to Tableau?

KNIME Analytics Platform is an open-source data analytics and workflow automation tool focused on data processing, machine learning, and predictive modeling, while Tableau is a data visualization software designed for creating interactive dashboards and reports. Job roles involving KNIME often require data science skills and knowledge of scripting languages, whereas Tableau roles emphasize data visualization and business intelligence expertise.

Is data science in demand?

Data science is highly in demand in the USA, with roles frequently requiring skills in analytics platforms like KNIME, Python, or R. The field offers strong job growth, competitive salaries, and opportunities across various industries such as finance, healthcare, and technology.
More about Knime Analytics Platform jobs
What cities are hiring for Knime Analytics Platform jobs? Cities with the most Knime Analytics Platform job openings:
What states have the most Knime Analytics Platform jobs? States with the most job openings for Knime Analytics Platform jobs include:
Infographic showing various Knime Analytics Platform job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 89% In-person, and 11% Hybrid job distribution, with an average salary of $77,722 per year, or $37.4 per hour.

Data Platform Engineer

BetWarrior

Glendora, NJ • On-site

$110K - $132K/yr

Other

Posted 23 days ago


Job description

Salary:

JOIN OUR TEAM

BetWarrior is a next-generation digital gaming company with a bold mission: to redefine the way people experience sports betting and casino entertainment across Latin America.

With a dynamic and diverse team, deep market insights, and cutting-edge technology, we're creating an experience that is personalized, responsible, and always player-first.

Great people, bold ideas, and a sharp focus on user experience set us apart


Purpose

We're looking for a Data Platform Engineer to shape and scale BetWarrior's data ecosystem as a strategic capability. This is a high-ownership, high-impact role: you'll define how we build, scale, and evolve our data platform and you'll drive the data foundations that power our product, analytics, and AI roadmap.


You'll work cross-functionally with Engineering, Product, BI, Data Science, Finance, Marketing, and Leadership. If you combine deep technical depth with strategic thinking and want to join a fast-growing environment with a clear track to expand your scope and long-term strategic impact this is your move.


In this role, youll

  • Design and own scalable data platforms for real-time and batch processing across Azure, AWS, and Snowflake.
  • Architect warehouse solutions, semantic layers, and data-sharing capabilities across domains.
  • Set the standards for data modeling, orchestration, lineage, observability, and quality.
  • Build the AI/ML data infrastructure: feature stores, training pipelines, vector databases, RAG architectures, and LLM-ready data products.
  • Evaluate and integrate AI-native tooling into the data platform.
  • Build and optimize robust ELT/ETL pipelines low-latency, trusted, business-critical.
  • Lead technical decisions on orchestration, CI/CD, and infrastructure automation.
  • Leverage AI-assisted development practices (code generation, automated testing, AI code review) to raise velocity and standards.
  • Build self-healing, self-optimizing pipelines using ML-driven observability.
  • Own monitoring, alerting, and operational excellence for the data platform.
  • Ensure compliance with governance, security, masking, and regulatory standards.
  • Collaborate closely with data leadership today to co-create BetWarrior's data platform strategy, with the mindset to own and drive its long-term evolution.
  • Influence technical and operational decisions, acting as a strategic partner to the business as the data domain scales.
  • Mentor and pair with engineers and analysts, raising engineering standards across the team.
  • Drive experimentation, personalization, fraud prevention, and player analytics capabilities.
  • Champion data culture and democratize data access across the company.


What we look for in an exceptional candidate

  • 7+ years in Data Engineering, Data Platform, or Analytics Engineering.
  • Snowflake expertise: performance optimization, architecture, governance, advanced platform capabilities.
  • Solid experience with Azure and AWS for large-scale data processing.
  • Expert-level SQL and strong Python skills.
  • Deep understanding of modern data architecture: dimensional modeling, semantic layers, distributed systems.
  • Experience with DataOps, CI/CD pipelines, infrastructure automation, and orchestration frameworks.
  • Experience building data infrastructure for AI/ML workloads (feature stores, vector DBs, or LLM integration).
  • Familiarity with AI-assisted engineering practices and tools.
  • Strong cross-functional stakeholder management and organizational communication skills.
  • Proven ability to mentor, elevate technical teams, and guide architectural vision.
  • You've been the go-to person for data architecture decisions in at least one previous org.
  • Excellent English communication skills. Fluency in Spanish is a valuable plus.


Bonus points if you also have

  • Experience in gaming, betting, fintech, or other high-volume transactional environments.
  • Hands-on experience with KNIME Analytics Platform.
  • Experience with semantic layer technologies (e.g., AtScale, dbt Semantic Layer).
  • Experience implementing AI-driven data quality, anomaly detection, or automated pipeline optimization.
  • Background in building self-service analytics ecosystems or experimentation frameworks.


We expect every team member to live our values

Accountability & Ownership Take charge, own your craft

Reliability Deliver with quality and consistency

Teamwork Collaborate, challenge, and grow together

Winner Spirit Compete with purpose and grit

Wellbeing Build a career that energizes you

Curiosity & Innovation Keep questioning. Keep improving