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Manager Data Analytics Engineer Jobs in Ohio (NOW HIRING)

Analytics Engineer, Care Operations

Columbus, OH · On-site

$67K - $90K/yr

Analytics Engineer, Care Operations Full Time - Exempt Columbus, Ohio AndHealth is on a mission to ... managing chronic, often life-altering conditions. When you catch a data quality issue before it ...

Analytics Engineer, Care Operations

Columbus, OH · On-site

$67K - $90K/yr

Analytics Engineer, Care Operations Full Time - Exempt Columbus, Ohio AndHealth is on a mission to ... managing chronic, often life-altering conditions. When you catch a data quality issue before it ...

Quanex is looking for a Manager, Data Governance to join our team located in Akron, OH, Owatonna ... analysis, and remediation * Partner with Engineering and Manufacturing teams to align data ...

Quanex is looking for a Manager, Data Governance to join our team located in Akron, OH, Owatonna ... analysis, and remediation * Partner with Engineering and Manufacturing teams to align data ...

Quanex is looking for a Manager, Data Governance to join our team located in Akron, OH, Owatonna ... analysis, and remediation * Partner with Engineering and Manufacturing teams to align data ...

Showing results 21-40

Manager Data Analytics Engineer information

What is a manager data analytics engineer?

A Manager Data Analytics Engineer is a professional who leads a team of data analytics engineers responsible for designing, building, and maintaining data systems and analytics solutions. They oversee data pipeline development, ensure data quality, and collaborate with stakeholders to translate business requirements into technical solutions. In addition to technical expertise, they manage project timelines, mentor team members, and help drive data-driven decision-making across the organization.

How does a manager data analytics engineer typically balance technical project work with team leadership responsibilities?

As a Manager Data Analytics Engineer, you are expected to split your time between overseeing complex analytics engineering tasks and guiding your team’s development. This involves setting project priorities, conducting code reviews, and ensuring data solutions align with business goals, while also mentoring team members and facilitating collaboration with stakeholders like data scientists and business analysts. Successful managers often establish clear communication channels and delegate tasks effectively, so they can stay hands-on with key projects while supporting the professional growth of their team.

What are the key skills and qualifications needed to thrive as a manager data analytics engineer, and why are they important?

To thrive as a Manager Data Analytics Engineer, you need a strong background in data engineering, analytics, and leadership, typically with a degree in computer science or a related field. Familiarity with tools like SQL, Python, data warehousing platforms (e.g., Snowflake, Redshift), and certifications in cloud technologies or data management are common requirements. Excellent communication, problem-solving, and team management skills set top performers apart in this role. These competencies are essential for driving data strategy, ensuring data quality, and leading analytics teams to deliver actionable business insights.

What is the difference between Manager Data Analytics Engineer vs Data Analytics Engineer?

AspectManager Data Analytics EngineerData Analytics Engineer
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often leadership experienceBachelor's or Master's in Data Science, Analytics, or related field
Work EnvironmentLeads teams, manages projects, collaborates with stakeholdersDevelops data models, analyzes data, implements solutions
Employer & Industry UsageUsed in tech, finance, healthcare, and large enterprisesCommon in similar industries, often within data teams

The main difference is that a Manager Data Analytics Engineer oversees teams and projects, focusing on leadership and strategic planning, while a Data Analytics Engineer primarily develops and implements data solutions. Both roles require strong technical skills, but the manager role adds a layer of team management and stakeholder communication.

What are the most commonly searched types of Data Analytics Engineer jobs in Ohio?

The most popular types of Data Analytics Engineer jobs in Ohio are:

What are popular job titles related to Manager Data Analytics Engineer jobs in Ohio?

For Manager Data Analytics Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Manager Data Analytics Engineer jobs in Ohio look for?

The top searched job categories for Manager Data Analytics Engineer jobs in Ohio are:

What cities in Ohio are hiring for Manager Data Analytics Engineer jobs?

Cities in Ohio with the most Manager Data Analytics Engineer job openings:

Analytics Engineer, Care Operations

AndHealth

Columbus, OH • On-site

$67K - $90K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 6 days ago


Job description

Analytics Engineer, Care Operations

Full Time – Exempt

Columbus, Ohio 

 

AndHealth is on a mission to radically improve access and outcomes for the most challenging 

chronic health conditions, with the goal of making world-class specialty care accessible and affordable to all. We partner with health systems, community health centers, and independent practices to remove barriers to care to ensure all people have access to the care they deserve.

None of that happens without good data. Every model we build, every intervention we design, and every conversation our care teams have with a partner is only as strong as the data behind it. That's where you come in.

About the role

We're looking for an Analytics Engineer to be the dedicated data partner to our Care Delivery team — the people on the front lines of getting patients into care and keeping them there. You'll take raw clinical and operations data and turn it into something a care leader can actually use: a trusted number on a dashboard, a governed metric everyone agrees on, a model that surfaces a problem before it becomes a crisis.

This is an embedded data partner role that sits close to Care Delivery. You'll be just as comfortable deep in a dbt model or a gnarly SQL query as you are in a room with a VP, translating what the data means and what to do about it. If you like owning a domain end to end — from the metric definition in the semantic layer to the dashboard a leader checks every morning — this role is for you.

Impact

The dashboards and data products you build will directly shape how AndHealth delivers care to thousands of patients managing chronic, often life-altering conditions. When you catch a data quality issue before it reaches a report, you're protecting the integrity of decisions that affect real people's access to care. When you build the semantic layer that lets an analyst self-serve a trusted metric instead of waiting on you, you're multiplying the entire team's ability to act. This isn't dashboards for dashboards' sake — it's the infrastructure that lets Care Operations see what's working, fix what isn't, and prove the value we bring to the partners and patients who depend on us.
What you'll do:

  • Translate business decisions into metrics — work with stakeholders to understand the decision they're trying to make, help them articulate what they need, and define the governed metric that answers it.
  • Partner with stakeholders from several teams to generate actionable insights that improve AndHealth's value to our partners and patients.
  • Build internal and external reporting and dashboards that visualize what's happening, why it's happening, and what we should do next across pharmacy and care operations.
  • Develop the semantic layer in dbt — defining governed metric definitions, curated datasets, and self-service data products that analysts and stakeholders can consume directly.
  • Partner with Data and Software Engineering as a key consumer of the raw data — flagging upstream data quality issues and gaps, and helping shape staging transformations so data arrives in a usable form.
  • Build a thorough testing suite across the data platform: schema tests, data quality checks, anomaly detection, and SLA monitoring so stakeholders can trust what they see.
  • Partner with the client management team to build the value story for quarterly business reviews.
  • Become a domain expert in your assigned area (care operations), translating business logic into accurate, scalable dbt data models.
  • Proactively identify data quality issues, gaps in coverage, and opportunities to improve the reliability and usability of the data platform.
 

Education & Licensure Requirements:

  • Bachelor's degree in Computer Science, Economics, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience.
 

Other Skills or Qualifications:

  • 6+ years of data analysis or related experience with significant experience partnering directly with business stakeholders.
  • Proven ability to turn ambiguous business questions into concrete, governed metric definitions — comfortable leading the discovery conversation with stakeholders rather than just executing a spec.
  • Strong analytical instincts — able to interrogate data, identify anomalies, trace them to their source, and communicate findings clearly to technical and non-technical audiences.
  • Strong SQL proficiency — complex queries, CTEs, window functions, and performance-optimized transformations across large datasets.
  • Hands-on experience with dbt (Core or Cloud) — preferred.
  • Comfortable working within a dimensionally modeled warehouse — facts and dimensions, mart layers, and why transformations are separated into staging, intermediate, and mart layers — even if you haven't owned that architecture from the ground up.
  • Experience creating reporting systems and visualizations; advanced experience with Excel and other data systems.
  • Comfort working alongside ETL/ELT pipelines and partnering with data or software engineers on ingestion.
  • Experience with a BI tool (Omni, Looker, Metabase, or similar), especially defining governed metrics and data products — preferred.
  • Familiarity with healthcare data (clinical, pharmacy, billing, or claims from EHRs, TPAs, or pharmacy operating systems) — preferred.
  • Advanced data modeling experience — designing non-trivial dbt/SQL models that encode real business logic.
  • Experience with R or Python or another scripting language in data analysis work — preferred. 
  • Comfort working in ambiguous, fast-moving environments with competing priorities.
 

Here's what we'd like to offer you:

  • Equal investment and support for our people and patients.
  • A fun and ambitious growing environment with a culture that takes on important things, takes risks, and learns quickly.
  • The ability to demonstrate creativity, innovation, and conscientiousness, and find joy in working together.
  • A team of highly skilled, incredibly kind, and welcoming employees, every one of whom has something unique to offer.
  • We know that the overall success of our business is a collaborative effort, and we strive to provide ongoing opportunities for our employees to learn and grow, both personally and professionally.
  • Full-time employees are eligible to participate in our benefits package which includes Medical, Dental, Vision Insurance, Paid time off, Short- and Long-Term Disability, 401k match and more.
 

We are an equal opportunity and affirmative action employer. We embrace diversity and are committed to creating an inclusive environment for all employees. Applicants will be considered for employment without regard to race, religion, gender, gender identity, sexual orientation, national origin, age, disability, or veteran status.

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