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Remote Senior Data Engineer Jobs in Michigan (NOW HIRING)

Corning

$111K - $146K/yr

Bachelor's degree in Computer Science, Software Engineering, Information Technology, Data Science ... A hybrid role based in Obispado, Monterrey, with most work expected to be remote and office ...

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Remote Senior Data Engineer information

What is the difference between Remote Senior Data Engineer vs Data Scientist?

AspectRemote Senior Data EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science or related fields, certifications
Work EnvironmentData pipelines, ETL processes, cloud platformsData analysis, modeling, visualization tools
Industry UsageTech, finance, healthcare, e-commerceTech, marketing, research, finance

Remote Senior Data Engineers focus on building and maintaining data infrastructure, while Data Scientists analyze data to generate insights. Both roles often collaborate but serve different functions within data teams. Understanding these differences helps in choosing the right career path or job search focus.

What is a remote senior data engineer?

Remote Senior Data Engineers are experienced professionals who design, build, and maintain complex data systems and pipelines, but work from a location outside of the company's main office. They are responsible for ensuring reliable data flow, optimizing data storage, and supporting analytics, often collaborating with teams across different time zones. Their role typically involves advanced programming, data architecture, and the implementation of best practices in data engineering, all while working remotely. This position demands strong technical skills, excellent communication, and the ability to work independently.

How does a remote senior data engineer typically collaborate with distributed teams to ensure data pipeline reliability?

As a Remote Senior Data Engineer, collaboration with cross-functional, distributed teams is usually facilitated through agile project management tools, regular video meetings, and shared documentation platforms. You’ll often work closely with data scientists, analysts, and DevOps engineers to design, build, and maintain scalable data pipelines. Clear communication and proactive status updates are essential to ensure everyone stays aligned and issues are addressed quickly. Leveraging version control systems and automated testing also helps maintain the reliability and quality of the data infrastructure across different time zones.

What are the key skills and qualifications needed to thrive as a remote senior data engineer?

To thrive as a Remote Senior Data Engineer, you need advanced expertise in data engineering concepts, SQL, and programming languages like Python or Scala, along with a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data frameworks (like Spark or Hadoop), and relevant certifications are typically required. Excellent problem-solving, communication, and self-management skills are crucial for collaborating remotely and driving projects independently. These competencies ensure robust data pipelines, effective teamwork, and successful delivery of scalable data solutions in distributed environments.
What are the most commonly searched types of Senior Data Engineer jobs in Michigan? The most popular types of Senior Data Engineer jobs in Michigan are:
What are popular job titles related to Remote Senior Data Engineer jobs in Michigan? For Remote Senior Data Engineer jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Remote Senior Data Engineer jobs in Michigan look for? The top searched job categories for Remote Senior Data Engineer jobs in Michigan are:
What cities in Michigan are hiring for Remote Senior Data Engineer jobs? Cities in Michigan with the most Remote Senior Data Engineer job openings:
Remote Senior Data Engineer jobs near you
Infographic showing various Remote Senior Data Engineer job openings in Michigan as of August 2026, with employment types broken down into 91% Full Time, and 9% Contract. Highlights an 100% Remote job distribution.

Senior Product Manager, Life Sciences Data Products

Beacon Talent

Detroit, MI • On-site, Remote

$152K - $158K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Senior Product Manager, Life Sciences Data Products (Applied AI)

Location: U.S. (Remote-first) with optional hub-based hybrid
Employment: Full-time
Level: Senior IC (high ownership)
Start: ASAP / Flexible

Beacon Talent is leading a confidential search for a venture-backed company building an applied AI + data platform that supports life sciences teams (biopharma, medtech, and research organizations) with secure access to real-world clinical datasets and tooling that accelerates discovery and development while maintaining high standards for privacy, quality, and responsible use.

The Role

As Senior Product Manager, Life Sciences Data Products, you will own the strategy and execution for a portfolio of data-driven products used by life sciences customers to find, access, evaluate, and operationalize complex clinical datasets for R&D and clinical development workflows.

This is a hands-on, high-agency role—ideal for a PM who loves ambiguous problem spaces, can translate market signals into crisp product bets, and can partner deeply with engineering and data teams to ship scalable product capabilities.

What You’ll Own

  • Product vision & roadmap: Define the life sciences product strategy, identify the highest-leverage problems, and translate them into a sequenced roadmap with measurable outcomes.

  • Discovery & validation: Run customer interviews, workflow mapping, and opportunity sizing to determine what to build, what to standardize, and what to avoid as one-off services.

  • Scalable data products: Build repeatable “productized” capabilities that improve dataset usability, governance, search/retrieval, cohort building, and downstream analytics readiness.

  • AI-assisted workflows: Partner with technical teams to design automation that reduces friction in data access and analysis (e.g., metadata enrichment, quality signals, dataset packaging, evaluation tooling).

  • Execution leadership: Write requirements, define success metrics, manage tradeoffs, and drive delivery from concept through launch—iterating based on usage and customer outcomes.

  • Cross-functional alignment: Collaborate closely with go-to-market partners to ensure positioning, packaging, and feedback loops inform the roadmap without turning the product into custom projects.

  • Market awareness: Stay current on life sciences R&D and clinical development trends and incorporate them into differentiation and product choices.

What We’re Looking For

Required

  • 5+ years building data products or platforms for life sciences and/or healthcare customers.

  • Strong product discovery muscle: customer interviews, problem framing, prioritization, and roadmap ownership.

  • Technical fluency across data infrastructure, APIs, pipelines, and working concepts in ML-enabled products (no need to code).

  • Track record partnering with engineering and data teams to deliver complex, high-impact product work.

  • Excellent communication—credible with technical teams and clear with non-technical stakeholders.

  • Comfort operating in a fast-moving environment with evolving inputs and limited process.

Nice to have

  • 0→1 product experience or taking early products to scale in a regulated domain.

  • UX/product design sensibility with strong intuition for end-user workflows.

  • Prior experience in analytics, data science, or experimentation.

  • Familiarity with privacy, governance, and quality frameworks for sensitive datasets.

Why This Role

  • Direct ownership of a high-impact roadmap at the intersection of life sciences + data platforms + applied AI

  • Meaningful influence over what becomes productized vs. service-heavy

  • Close collaboration with technical leadership and high visibility across the company

Compensation

Competitive base + equity + benefits. (Exact range varies by level and location and will be shared during the process.)