1

Data Engineering Consultant Jobs in Ohio (NOW HIRING)

$69.64 - $92.85/hr

Additionally, you'll learn to translate simple hypotheses into engineered features, manage secure data environments, and contribute to R&D initiatives focused on innovating and scaling ...

Assign, review, and evaluate laboratory or field data for inclusion in reports. Apply sound ... Senior Consulting level engineering professional who acts as a resource and specialist in the ...

$69.24 - $92.31/hr

... Consultant - Data Engineering (m/w/d). Der Elevator Pitch für Deinen Traumjob Unbefristet ab sofort Vollzeit 30 Tage Urlaub Deine Benefits Bei uns arbeitest Du in einem Team, das Deine Interessen im ...

Assign, review, and evaluate laboratory or field data for inclusion in reports. Apply sound ... Senior Consulting level engineering professional who acts as a resource and specialist in the ...

You'll be a key contributor to collecting data prior to field execution and construction management ... Consultant, Science/Engineering position, the anticipated annual base pay is $74,250-$103,128 (USD)

You'll be a key contributor to collecting data prior to field execution and construction management ... Consultant, Science/Engineering position, the anticipated annual base pay is $74,250-$103,128 (USD)

Data Services Integration Engineer Join the Legal Tech Revolution at Litera Are you ready to shape ... consultants and customer resources to manage issue logs and lead issue review meetings with ...

next page

Showing results 1-20

Data Engineering Consultant information

See Ohio salary details

$11

$42

$74

How much do data engineering consultant jobs pay per hour?

As of Aug 30, 2026, the average hourly pay for data engineering consultant in Ohio is $42.68, according to ZipRecruiter salary data. Most workers in this role earn between $28.80 and $57.12 per hour, depending on experience, location, and employer.

What does a data engineering consultant do?

A Data Engineering Consultant helps organizations design, build, and optimize systems for collecting, storing, and analyzing large volumes of data. They work with clients to understand their data needs, recommend appropriate technologies, and implement solutions that support data-driven decision making. Their role often includes integrating data from different sources, ensuring data quality, and optimizing data pipelines for performance and scalability. Data Engineering Consultants also provide guidance on best practices and may assist in training in-house teams.

What are the key skills and qualifications needed to thrive as a data engineering consultant?

To thrive as a Data Engineering Consultant, you need strong programming skills (e.g., Python, SQL), expertise in data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), ETL tools, and data warehousing systems is typically required, along with relevant certifications. Excellent problem-solving, communication, and project management skills help consultants effectively translate business needs into technical solutions and collaborate with stakeholders. These skills are crucial for designing robust, scalable data architectures that drive actionable insights and meet client objectives.

What are some common challenges faced by data engineering consultants when working with clients, and how can they be addressed?

Data Engineering Consultants often encounter challenges such as integrating data from disparate sources, ensuring data quality, and aligning technical solutions with client business goals. Successfully addressing these issues involves strong communication skills to clarify requirements, a deep understanding of modern data platforms, and the ability to recommend scalable architectures. Building trust with stakeholders and proactively managing expectations are also key to overcoming obstacles and delivering impactful results.

What is the difference between Data Engineering Consultant vs Data Analyst?

AspectData Engineering ConsultantData Analyst
Required CredentialsBachelor's/Master's in CS, Data Science, or related; certifications like AWS, Azure, GCPBachelor's in Statistics, Math, or related; certifications like Microsoft Data Analyst
Work EnvironmentDesigning data pipelines, building infrastructure, working with cloud platformsAnalyzing data sets, creating reports, visualizations, and insights
Employer & Industry UsageTech companies, consulting firms, finance, healthcareMarketing agencies, finance, retail, healthcare

While both roles work with data, Data Engineering Consultants focus on building and maintaining data infrastructure, whereas Data Analysts interpret data to provide insights. The roles often collaborate but require different skill sets and tools.

What are popular job titles related to Data Engineering Consultant jobs in Ohio?

For Data Engineering Consultant jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Data Engineering Consultant jobs in Ohio look for?

The top searched job categories for Data Engineering Consultant jobs in Ohio are:

Infographic showing various Data Engineering Consultant job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $88,777 per year, or $42.7 per hour.

Data Engineering Consultant - QuantumBlack, AI by McKinsey

On-site


McKinsey & Company, Inc.
Business Management Consulting • 10K+ employees

8.5

Company rating: 8.5 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

21st of 72 rated business consultants

Good employer

Respectful managers

Good training


$69.64 - $92.85/hr

Other

Posted 12 days ago


Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem‑solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will build the foundational data infrastructure that powers cutting‑edge AI applications leveraging LLMs, retrieval systems, workflows, and emerging agentic architectures. You will design and maintain scalable data pipelines, manage secure data environments, and prepare data for AI‑driven systems while collaborating with cross‑functional teams and clients. You’ll tackle real‑world challenges by contributing to the development of next‑generation AI systems and grow as a technologist by working alongside diverse experts across industries. You will design and build the scalable, reproducible data components essential for machine learning, agentic, and autonomous AI systems. You’ll assess data landscapes, apply data quality fundamentals, and prepare data for AI solutions. Additionally, you’ll learn to translate simple hypotheses into engineered features, manage secure data environments, and contribute to R&D initiatives focused on innovating and scaling next‑generation AI capabilities. Your work will help solve some of the most complex and high‑impact challenges facing clients across industries. Collaborating across McKinsey’s QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you’ll help develop innovative AI capabilities and scalable enterprise solutions. You’ll help build robust data foundations for scalable, production‑ready AI systems. Your contributions will directly support the firm’s ability to accelerate AI adoption, solve complex business problems at scale, and enable clients to achieve meaningful, lasting impact. You’ll be based in Germany as part of our global Data Engineering community. Working in cross‑functional Agile teams, you’ll collaborate closely with Data Scientists, Machine Learning Engineers, and industry experts to deliver AI solutions. By partnering with clients—from data owners to C‑level executives—you’ll help solve complex problems that drive tangible business value and begin to build your skills as a client‑facing technologist. You will grow at the forefront of AI, data engineering, and emerging agentic technologies. You’ll develop expertise at the intersection of technology and business by tackling diverse challenges in the evolving AI landscape. Working alongside multidisciplinary teams, you’ll gain a holistic understanding of how data engineering enables advanced AI while collaborating with leading AI and data experts in the industry.

YOUR GROWTH

Driving lasting impact and building long‑term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture—doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward. In return for your drive, determination, and curiosity, we’ll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you’ll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

  • Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast‑paced learning experience, owning your journey.
  • A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World‑class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well‑being for you and your family.
YOUR QUALIFICATIONS AND SKILLS
  • Degree in Computer Science/Engineering, or equivalent experience
  • 2+ years of relevant professional experience building and deploying data solutions
  • Strong proficiency in Python and SQL for data engineering and experience writing robust, production‑grade code, including deploying code across environments
  • Proven experience building end‑to‑end data pipelines and platforms for Agentic AI, Generative AI, Machine Learning, or Business Intelligence, covering data preparation, embeddings generation, vector search, and system integration using modern frameworks (Spark, dbt, LangChain)
  • A strong foundation in system design, data storage, and reliability with commonly used data platforms (Databricks, Snowflake, BigQuery, PSQL, etc.) and data engineering tools (e.g., Pandas, Spark, dbt, etc.)
  • Hands‑on experience with MLOps/LLMOps principles, including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform)
  • Experience building systems with different data formats (structured vs unstructured) and data processing methods (streaming vs batch) and deploying across major cloud platforms (AWS, Azure, GCP)
  • Exceptional time management in a complex and largely autonomous work environment
  • Commercial client‑facing or senior stakeholder management experience is beneficial
  • Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
  • Strong communication skills, both verbal and written, in German and English

FOR U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by applicable law.

FOR NON‑U.S. APPLICANTS: McKinsey & Company is an Equal Opportunity employer. For additional details regarding our global EEO policy and diversity initiatives, please visit our McKinsey Careers and Diversity & Inclusion sites.

#J-18808-Ljbffr

McKinsey logo

About McKinsey

Sourced by ZipRecruiter

In April 2021, we announced the launch of McKinsey Sustainability, our new client-service platform with the goal of helping all industry sectors transform to get to net zero by 2050 and to cut carbon emissions by half by 2030. McKinsey Sustainability seeks to be the preeminent impact partner and advisor for our clients, from the board room to the engine room, on sustainability, climate, energy transition, and environmental, social and governance (ESG). We are committed to invest behind this goal over the next four years-through our client service, knowledge and capability building, acquisitions and alliances as well as pro-bono investments.

Industry

Business management consulting

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Social media


What McKinsey & Company employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom