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Contract Data Engineering Jobs in Ohio (NOW HIRING)

Guidehouse

Data Engineer

Beavercreek, OH

$53K - $88K/yr

Continuously develop technical skills and stay current with emerging data engineering technologies and best practices. * Role contingent upon contract award What You Will Need: * U.S. Citizenship or ...

Medpace

Data Engineer

Cincinnati, OH · On-site

$111K - $134K/yr

Medpace is a full-service clinical contract research organization (CRO) providing clinical development services to the biotechnology, pharmaceutical, and medical device industries. The Data Engineer ...

A-TEK Inc.

Health IT Data Engineer

Continental, OH · Remote

$125K - $135K/yr

Minimum seven (7) years of data engineering experience. * Strong SQL development skills ... Employment is contingent upon contract award and successful completion of any required background ...

Guidehouse

Data Engineer Lead

Beavercreek, OH · On-site

Define technical architecture, engineering standards, and best practices for data integration ... Role is contingent upon contract award What You Will Need: * U.S. Citizenship or Green Card is ...

Booz Allen Hamilton

Data Engineer

Dayton, OH · On-site

$61K - $141K/yr

You Have: * 5+ years of experience with data architecture, design, or engineering projects ... as well as contract-specific affordability and organizational requirements. The projected ...

Kanak Elite Services Inc

Lead Data Engineer

Cincinnati, OH · On-site

$98K - $129K/yr

Type: Contract Required Skills: Azure Databricks PySpark Delta Lake Unity Catalog CI/CD (Data Engineering) Enterprise Data Architecture Interview Process: Face-to-Face interview required Travel ...

GHR Healthcare

Senior Data Engineer

Columbus, OH · On-site

$99K - $134K/yr

Contract-to-Hire Position Overview We are seeking an experienced Senior Data Engineer to join a large, enterprise healthcare organization in Columbus, Ohio. This individual will help design, develop ...

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Contract Data Engineering information

What is contract data engineering?

Contract data engineering refers to hiring data engineers on a temporary or project basis, rather than as full-time employees. Contract data engineers are responsible for designing, building, and maintaining data pipelines, databases, and other infrastructure to support data analytics and business needs. Companies often hire contract data engineers to handle specific projects, scale up teams quickly, or bring in specialized skills for a limited time. This arrangement offers flexibility for both the company and the engineer, and is common in industries with fluctuating data workloads or short-term projects.

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

To thrive as a Contract Data Engineer, you need strong proficiency in data modeling, ETL processes, and programming languages such as Python or SQL, often supported by a degree in computer science or a related field. Familiarity with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and relevant certifications like Google Cloud Professional Data Engineer are typically required. Excellent problem-solving, adaptability, and effective communication are crucial soft skills in this role. These competencies enable efficient project delivery, seamless collaboration with stakeholders, and the ability to quickly adapt to new technical environments and client requirements.

What are some common challenges faced by contract data engineers and how can they be addressed?

Contract data engineers often face the challenge of quickly familiarizing themselves with a company's existing data infrastructure and processes. Since contracts are typically short-term, there is limited time to onboard, understand unique data pipelines, and build relationships with stakeholders. To address this, successful contract data engineers proactively communicate with team members, document their work thoroughly, and leverage their prior experience with a variety of tools and platforms. Flexibility and strong problem-solving skills are essential for adapting to new environments and delivering results efficiently.

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

AspectContract Data EngineeringData Analyst
Required SkillsSQL, Python, ETL, cloud platforms, data pipeline developmentSQL, Excel, data visualization, reporting tools
Work EnvironmentProject-based, technical teams, cloud or on-premises infrastructureBusiness units, reporting teams, often in office or remote
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Contract Data Engineers focus on building and maintaining data pipelines and infrastructure, requiring technical skills in programming and cloud platforms. Data Analysts interpret data, create reports, and visualize insights, often using different tools. While both roles work with data, Contract Data Engineering is more technical and infrastructure-oriented, whereas Data Analysts focus on data interpretation and business insights.

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

The most popular types of Data Engineering jobs in Ohio are:

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

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

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

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

What cities in Ohio are hiring for Contract Data Engineering jobs?

Cities in Ohio with the most Contract Data Engineering job openings:

Contract Data Engineering jobs near you
Infographic showing various Contract Data Engineering job openings in Ohio as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 82% Physical, 4% Hybrid, and 14% Remote job distribution.

Sr. Manager, Data Engineering

Highland Heights, OH

Park Place Technologies
IT Services • 1 - 5K employees

7.8

Company rating: 7.8 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

88th of 226 rated it services

Great coworkers

Good employer

Respectful managers

Learn more about Park Place Technologiesexternal

Full-time

Re-posted 4 days ago

Job description

Sr. Manager, Data Engineering

The Sr. Manager, Data Engineering is a key senior leader responsible for the strategy, architecture, and execution of the enterprise data engineering function. This leader will build and scale a high-performing team, drive strategy and design of the data engineering framework for reporting needs, facilitates strategy around the data warehouse, partners with other IT leaders to provide availability of data for AI/ML initiatives, assists with business intelligence, and core operational systems for seamless reporting. Reporting to senior technology leadership, this role serves as a strategic partner to IT, Analytics, and business stakeholders to ensure data is reliable, governed [in partnership with master data management], and accessible at scale.

This is a high-impact opportunity for a technically grounded, people-first leader who thrives in a fast-paced environment and is energized by building scalable systems during a period of significant growth, including M&A integration and cloud transformation.

Responsibilities:

  • Leadership & Strategy
    • Define and drive the enterprise data engineering roadmap, aligned to business and technology goals
    • Build, lead, and mentor a multi-disciplinary team of data engineers (10-15) and product owner(s) (1-2)
    • Partner with the CIO, Analytics, AI, and business leadership to prioritize and deliver data capabilities
    • Establish engineering standards, best practices, and an operational excellence framework across the data organization
    • Champion a culture of data quality, engineering rigor, and continuous improvement
  • Platform & Architecture
    • Architect and oversee scalable data pipelines, data lakes, warehouses, and real-time streaming infrastructure
    • Lead cloud-native data platform strategy and adoption across Azure, AWS, or GCP environments
    • Own the selection, implementation, and lifecycle management of data engineering tools and platforms
    • Ensure data platform reliability, performance, and cost efficiency at scale
    • Partner with Platform Development Architects and leadership on integration patterns across key enterprise systems, including ERP, ServiceNow, and supply chain platforms
  • Data Governance & Quality
    • Own and evolve the enterprise data governance framework, including data lineage, cataloging, and access controls
    • Define and enforce data quality standards, measurement, and remediation processes
    • Partner with Security and Legal to ensure compliance with data privacy regulations and policies
    • In partnership with the Director of Development and AI, drive adoption of clean, governed, AI-ready data as a core organizational asset.
  • Delivery & Operations
    • Manage team delivery across multiple concurrent programs, including integration workstreams from M&A activity
    • Lead data engineering support for AI/ML platform enablement 
    • Oversee vendor relationships, contracts, and budget for data infrastructure and tooling
    • Establish SLAs, incident management, and monitoring for data platform operations

Basic Qualifications:

  • 10+ years of progressive experience in data engineering, data architecture, or a related technical discipline
  • 5+ years of people leadership experience, including managing and developing senior engineers and managers; Communication is a critical facet for this role with an ability to manage up, to the side or down.
  • Proven track record of architecting and delivering enterprise-scale data platforms in production
  • Deep expertise in modern data stack tooling (e.g., Azure SQL, Azure Fabric, Kafka, Snowflake, Databricks, or equivalents)
  • Strong cloud data platform experience on Azure, AWS, or GCP
  • Demonstrated experience in data governance programs and data quality frameworks
  • Ability to translate complex business requirements into pragmatic technical strategy and roadmaps
  • Strong executive communication skills; comfortable presenting to C-suite and board-level audiences
  • Experience operating in dynamic, growth-stage environments, including M&A integration preferred
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field; Master’s preferred

Preferred Qualifications:

  • Experience in IT services, managed services, or enterprise technology industries
  • Familiarity with ERP, ServiceNow, or supply chain data ecosystems
  • Experience leading data strategy and integration through M&A events
  • Exposure to data mesh, data product, or federated governance models
  • Relevant certifications in cloud data platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate)
  • A strategic mindset paired with a bias for action and hands-on delivery
  • Passion for building reliable, scalable, and well-governed data systems
  • A collaborative and inclusive leadership style with the ability to influence across levels
  • Intellectual curiosity and a continuous improvement mindset
  • High standards for data quality and a commitment to engineering excellence

Travel: 

  • 15%

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