AI Data Engineer Jobs in Ohio
AI Data Engineer jobs in Ohio are in strong and growing demand, with concentrated hiring in financial services, healthcare, manufacturing technology, and logistics across a seniority range from entry-level data associates through senior and principal engineers. Columbus, Cleveland, and Cincinnati anchor most of the hiring, where established employers like Nationwide Insurance, KeyBank, and Procter & Gamble maintain substantial data and analytics teams. The most sought-after specialties in Ohio right now are real-time data pipeline development, MLOps infrastructure, and cloud-native data platform engineering on AWS and Azure. Find a role that fits below and apply directly.
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A senior Microsoft-focused consulting role spanning discovery, architecture, engineering, governance, and client enablement.
~ Client-Facing (Discovery/Architecture/Delivery)
~ Microsoft Cloud (Azure & Microsoft Fabric)
~ Data Engineering (Trusted Data Foundations for Analytics & AI)
Interlink Cloud Advisors is looking for a Senior Data & AI Engineering Consultant to help clients build modern, scalable data platforms on Microsoft Azure and Microsoft Fabric. In this client-facing role, you'll lead discovery, design pragmatic architectures, and deliver end-to-end solutions that turn raw data into trusted, analytics-ready datasets for BI, reporting, advanced analytics, and AI use cases. You'll work across Fabric (OneLake, Lakehouse, Warehouse) and Azure data services to ensure solutions are secure, governed, maintainable, cost-conscious, and operationally ready.
WHAT YOU'LL DO
- Lead client discovery to understand business goals, the data landscape, constraints, and success metrics, then translate findings into a clear delivery plan.
- Design and recommend data lake, lakehouse, data warehouse, and analytical data store architectures on Azure and Microsoft Fabric aligned to client needs.
- Implement, or guide implementation of, ingestion, transformation, and orchestration pipelines using Microsoft Fabric experiences and Azure services such as Data Factory, Synapse, and Databricks.
- Integrate data from operational systems, APIs, and third-party sources and transform raw data into curated datasets ready for consumption.
- Build and maintain analytics-ready data models and schemas; implement enrichment, business rules, and reusable patterns for consistency across projects.
- Enable multiple compute engines - SQL, Spark/PySpark, Spark SQL, and KQL - against shared datasets to support diverse analytics scenarios.
- Prepare governed data products and reusable datasets for BI, advanced analytics, and AI use cases, including retrieval-ready data patterns when relevant.
- Establish data quality practices, including validation, reconciliation, testing, and monitoring; troubleshoot failures and continuously improve pipeline resiliency.
- Optimize transformations, query performance, and pipeline execution to meet client service level and cost objectives.
- Implement logging, metrics, and operational runbooks, and support deployments, cutovers, and hypercare as needed.
- Design and implement security, governance, and compliance controls, including access, least privilege, data protection, and lineage across Azure and Fabric.
- Facilitate workshops and communicate architecture tradeoffs, partnering with client stakeholders, architects, analysts, and BI developers to deliver trusted datasets.
- Produce clear consulting deliverables, including design documents, diagrams, implementation guides, and enablement materials, to support adoption and a smooth handoff.
Required Qualifications
- Experience designing and delivering modern analytics platforms using lakehouse and/or data warehouse patterns on Azure and/or Microsoft Fabric, including client-facing delivery.
- Strong SQL skills with experience building transformations and dimensional or analytical models.
- Hands-on experience with Spark (PySpark/Spark SQL) and/or KQL for data engineering and analytics workloads.
- Experience applying software engineering practices to data solutions, including modular design, source control, automated testing, code review, and technical documentation.
- Experience building reliable data pipelines, including orchestration, scheduling, error handling, and automated monitoring.
- Knowledge of data quality practices, including validation, reconciliation, testing, incident triage, and root-cause analysis.
- Working knowledge of Power BI, including semantic modeling concepts, to support end-to-end analytics delivery; Power Apps experience is a plus.
- Understanding of security and governance concepts for data platforms, including access controls, least privilege, compliance, and lineage.
- Strong communication skills, with the ability to present recommendations, align stakeholders, and manage expectations in a client environment.
Preferred Qualifications
- Direct experience with Microsoft Fabric components - OneLake, Lakehouse, Warehouse, Data Factory in Fabric, and Real-Time Analytics/KQL databases - including platform administration, capacity planning, and standards.
- Experience with Azure services commonly used in data platforms, such as Azure Data Factory, Synapse, Databricks, ADLS Gen2, and Key Vault.
- Working knowledge of Azure architecture fundamentals across identity, networking, storage, monitoring, resiliency, and cost management.
- Familiarity with AI-enablement patterns - such as preparing governed enterprise data for Azure AI Search or Microsoft Foundry, retrieval-augmented generation, or agent-based solutions—is valued. Deep agent application development experience is not required.
- Experience implementing CI/CD and Infrastructure as Code, including environment strategy and release management for data solutions.
- Familiarity with semantic modeling and BI enablement patterns, including Power BI datasets, self-service analytics, and governance guardrails.
- Current Microsoft certifications relevant to the role are valued, especially Microsoft Certified: Fabric Data Engineer Associate (DP-700), Microsoft Certified: Power BI Data Analyst Associate (PL-300), and, for broader architecture responsibilities, Microsoft Certified: Azure Solutions Architect Expert (AZ-305). Equivalent current Microsoft credentials and experience mentoring or enabling client teams are also welcome.
About Us
Interlink is a nationally recognized IT consultancy, offering the flexibility of a small company while providing stability and benefits usually found at enterprise firms. We work with a "family first" attitude, so we look to hire motivated individuals who understand that getting work done while having fun is important. As the winner of The Best Places to Work Award for five consecutive years, we know what it takes to care for our employees and clients.
Interlink Advantage
We are the premier Microsoft Cloud consulting company based in Mason, OH. We are a team of trusted experts who know how to navigate the intricacies of Microsoft's technologies, guiding and educating clients to avoid overspending on tech licenses while optimizing their tools. At Interlink, we believe working in an innovative, fun, and collaborative environment is key to success. Get to know us and our company culture more at: http://www.interlink.com/about-us/company-culture.
Interlink Cloud Advisors is an equal-opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability status.
See All 32 AI Data Engineer Jobs in Ohio
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Find AI Data Engineer JobsAI Data Engineer Jobs by City in Ohio
Where Ohio roles are concentrated, by current openings.
AI Data Engineer Job Market in Ohio
A snapshot from current Ohio openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Banking & Financial Services
- Technology & Software
What Ohio Employers Look For
The qualifications that appear most often in AI data engineer jobs across Ohio.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Proficiency in Python and SQL with hands-on experience building production data pipelines
- Experience with cloud data platforms such as AWS, Azure, or Google Cloud
- Familiarity with machine learning frameworks and model deployment workflows in enterprise environments
- Experience with orchestration tools such as Apache Airflow, dbt, or equivalent pipeline management systems
- Strong communication skills to collaborate with data scientists, analysts, and business stakeholders
AI Data Engineer Jobs in Ohio: Frequently Asked Questions
How do you become a ai data engineer in Ohio?
There is no state-issued license required to work as an ai data engineer in Ohio. The typical path is a bachelor's degree in computer science, data science, or a related field, followed by hands-on experience with cloud platforms and data pipeline tools. Ohio universities including Ohio State, Case Western Reserve, and the University of Cincinnati offer relevant programs. Earning cloud certifications from AWS or Microsoft Azure strengthens a candidate's profile with most Ohio employers.
How much do AI data engineers make in Ohio?
AI data engineers in Ohio earn a median of about $102,630 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $61,710 for the lowest 10% to over $160,650 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire ai data engineers in Ohio?
Employers hiring ai data engineers in Ohio right now include Lubrizol, Accenture, and Northwest Bank, based on current listings on Migrate Mate as of November 2026. Ohio's mix of Fortune 500 headquarters, large regional banks, and major health systems means demand stays consistent across multiple industries rather than depending on a single sector.
Which Ohio cities have the most ai data engineer jobs?
Cincinnati, Columbus, and Cleveland have the most ai data engineer openings in Ohio. Columbus leads as the state capital and home to major insurance, fintech, and retail headquarters, while Cleveland's concentration of health systems and financial institutions drives strong demand, and Cincinnati benefits from large consumer goods and logistics employers anchored by companies like Procter & Gamble and Kroger.
Are there remote ai data engineer jobs in Ohio?
Yes, and more than most fields. About 56% of ai data engineer openings tied to Ohio are remote or hybrid as of November 2026, reflecting how much of the work involves code, cloud infrastructure, and data systems that don't require physical presence. Pipeline development, model monitoring, and platform engineering roles are the most consistently offered in remote or hybrid formats.
How can I get hired as a ai data engineer in Ohio with little or no experience?
The most realistic entry path is targeting associate or junior data engineer roles at Ohio's large financial and healthcare employers, who regularly hire new graduates from Ohio State, Case Western Reserve, and University of Dayton into rotational analyst or data operations programs. Building a portfolio of end-to-end pipeline projects on GitHub and earning an AWS Cloud Practitioner or Azure Data Fundamentals certification meaningfully improves competitiveness. Adjacent roles like data analyst, BI developer, or data operations specialist at Ohio companies also serve as common stepping stones into engineering positions.
Where can I find and apply to ai data engineer jobs in Ohio?
You can find and apply to ai data engineer jobs in Ohio on Migrate Mate, which lists current Ohio openings updated regularly. Search the listings for roles that match your experience and location, then apply directly to the ones that fit.
See All 32 AI Data Engineer Jobs in Ohio
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