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Remote Amazon Business Intelligence Engineer Jobs in Ohio

Kobie Marketing

AI Engineer

Columbus, OH · Remote

Join a National Top Workplace Named a Top Workplace in the USA and Top Remote Workplace, Kobie is ... We're building an internal agent platform on Amazon AgentCore that automates analyst workflows ...

Medpace, Inc.

Data Engineer

Cincinnati, OH · On-site +1

$109K - $132K/yr

Utilize skills in development areas including data warehousing, business intelligence, and databases (Snowflake, ANSI SQL, SQL Server, T-SQL); * Support programming/software development using Extract ...

Medpace, Inc.

Junior Data Engineer

Cincinnati, OH · On-site +1

Utilize skills in development areas including data warehousing, business intelligence, and databases (Snowflake, ANSI SQL, SQL Server, T-SQL); * Support programming/software development using Extract ...

Medpace, Inc.

Senior Data Engineer

Cincinnati, OH · On-site +1

$101K - $138K/yr

Utilize skills in development areas including data warehousing, business intelligence, and databases (Snowflake, ANSI SQL, SQL Server, T-SQL); * Support programming/software development using Extract ...

Statheros

We are looking for a talented AI Engineer specializing in Proximal Policy Optimization (PPO) to ... Remote work location. * Competitive salary. * Flexible work schedule. * Opportunities for ...

Gifthealth Inc

Manager, Reporting & Analytics

Columbus, OH · Remote

$115K - $175K/yr

Experience : 6+ years of experience in analytics, business intelligence, or data engineering and 2+ ... Location : Remote Employment Classification Status: Full-time FLSA: Exempt Equal Employment ...

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All JobsAmazon Business Intelligence Engineer JobsRemote Amazon Business Intelligence Engineer JobsRemote Amazon Business Intelligence Engineer Jobs in Ohio

Remote Amazon Business Intelligence Engineer information

What are the key skills and qualifications needed to thrive as a remote Amazon Business Intelligence Engineer, and why are they important?

To thrive as a Remote Amazon Business Intelligence Engineer, you need strong analytical skills, expertise in data modeling, and proficiency in SQL and data visualization, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with Amazon Web Services (AWS), business intelligence tools like Tableau or QuickSight, and ETL systems is commonly required. Strong problem-solving abilities, effective communication, and self-motivation are essential soft skills for remote collaboration and translating business needs into actionable insights. These skills are crucial for driving data-informed decision-making and delivering impactful business solutions in a distributed work environment.

What is the difference between Remote Amazon Business Intelligence Engineer vs Remote Amazon Data Analyst?

AspectRemote Amazon Business Intelligence EngineerRemote Amazon Data Analyst
Required SkillsData modeling, SQL, BI tools, AWS servicesData querying, Excel, SQL, visualization tools
Work EnvironmentCross-functional teams, cloud-based platformsData-focused roles, reporting environments
Industry UsageTech, retail, e-commerceRetail, marketing, e-commerce

The Remote Amazon Business Intelligence Engineer focuses on designing and maintaining data systems and dashboards to support business decisions, often working with cloud platforms like AWS. In contrast, the Remote Amazon Data Analyst primarily interprets data, creates reports, and provides insights. Both roles require SQL and data visualization skills but differ in scope and technical depth.

What does a remote Amazon Business Intelligence Engineer do?

A Remote Amazon Business Intelligence Engineer is responsible for designing, developing, and maintaining data solutions that help Amazon make data-driven decisions. They work with large datasets, build dashboards, create data models, and generate reports to support different business teams. Their role often involves using tools like SQL, Python, and AWS services to extract and analyze data. Working remotely, they collaborate with stakeholders across Amazon to deliver insights that improve processes and drive business growth.

What are the main collaboration methods for a remote Amazon Business Intelligence Engineer working with cross-functional teams?

As a Remote Amazon Business Intelligence Engineer, effective collaboration is essential, especially when working with data scientists, product managers, and software engineers across different time zones. Most communication occurs through virtual meetings, project management platforms, and regular status updates via email or chat tools. You'll often participate in sprint planning sessions, data review meetings, and code reviews to ensure data solutions align with business objectives. Building strong remote relationships and maintaining clear, proactive communication are key to overcoming the challenges of working in a distributed team environment.
What are the most commonly searched types of Amazon Business Intelligence Engineer jobs in Ohio? The most popular types of Amazon Business Intelligence Engineer jobs in Ohio are:
What are popular job titles related to Remote Amazon Business Intelligence Engineer jobs in Ohio? For Remote Amazon Business Intelligence Engineer jobs in Ohio, the most frequently searched job titles are:
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What cities in Ohio are hiring for Remote Amazon Business Intelligence Engineer jobs? Cities in Ohio with the most Remote Amazon Business Intelligence Engineer job openings:
Remote Amazon Business Intelligence Engineer jobs near you

AI Engineer

Kobie Marketing

Columbus, OH • Remote

Full-time

Re-posted 25 days ago

Job description

Join a National Top Workplace 
 
Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We're always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world's most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. 
 
Join Us from Anywhere 
While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: 

         Flexible Time Off to recharge when needed 
         Nine Company-Wide Holidays 
         A diverse suite of benefits prioritizing your growth, development, and personal well-being 

Discover more about our perks and benefits here. 
 
Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. 


About the team and what we'll build together

Kobie runs some of the largest loyalty programs in the world. We're building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams and clients an LLM-native way to work with complex loyalty logic.

We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role. You'll prototype, ship, monitor, and iterate on features used by real teams

Our team tends to be people who reason carefully, ship working code,and pick up new tools without a lot of handholding. There's no single path into this role. We value the impact of what you've built and your track record of building things that hold up.

How you will make an impact

Agent Development

  • Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory
  • Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows and scenarios
  • Write the tools and skills agents use  API integrations, SQL queries against Snowflake, Snowflake backed knowledge retrieval with clear contracts and Pydantic validation

Evaluation and Reliability

  • Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations, and wire them into CI
  • Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation
  • You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks

Collaboration

  • Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex Search Services)
  • Contribute to refining our internal engineering patterns as the stack evolves

What you need to be successful

Required

  • 3+ years of professional Python, with production experience building and operating services
  • 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
  • Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel
  • Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
  • Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
  • Fluency with Git, Docker, and modern API frameworks
  • Clear written communication and the judgment to know when something is ready to ship

A bachelor's degree is not required. Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts.

Strongly Preferred

  • Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations
  • Experience with Snowflake, Snowpark, or Snowflake Cortex
  • Fluency in writing and reading SQL, as well as understanding semantic models.
  • Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop
  • A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer
  • Experience in Loyalty, MarTech, AdTech, or a comparable data rich B2B domain
Who we are  As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. 
 
A place for all We celebrate and embrace diversity at Kobie! 
Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. 
 
We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. 
 
Ready to join us? If you're ready to make an impact and grow in a supportive, innovative environment, we'd love to hear from you. Apply today and join the best and brightest in loyalty! 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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