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Contract Data Engineering Jobs in Ohio (NOW HIRING)

Columbus, Ohio - need local Onsite: 4 days a week Contract: 6 months to perm Interview process: 1 video interview then onsite panel interview Leads the data nimble team for their data warehouse.

Contract / Consulting Key Responsibilities Lead Data Architecture and Data Engineering Design end-to-end enterprise data architectures, including lakehouse, warehouse, streaming, and AI/ML ...

Data Engineer

Columbus, OH · On-site

$43.59 - $51.59/hr

Data Engineer Genesis10 is currently seeking a Data Engineer for a contract position with a Global Financial Institution located in Columbus, OH or Las Colinas, TX. This is a 12+ month contract ...

Cleveland, OH - 100% ONSITE Type of Hire : Long Term Contract Rate : $60/Hour Location: Cleveland, OH - 100% ONSITE Duration: 6 months Role: Data engineer Skills: Digital : Data Science~Data Quality ...

Data Engineer

Cincinnati, OH · Hybrid

$109.90K - $132K/yr

Contract to Hire (w2) Duration: 3-6 months contract then permanent role Along with the below skills ... Strong understanding of data engineering principles and software development lifecycle.

This is a hybrid 3-month contract-to-hire position with a client located in Columbus, OH. This role pays $60.00-$68.00 per hour, W2, based on skill and experience level. The Data Engineer Lead plays ...

Data Engineer

Cincinnati, OH · On-site

$111.70K - $134.20K/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 ...

Lead Data Engineer

Columbus, OH · On-site

$60 - $68/hr

This is a hybrid 3-month contract-to-hire position with a client located in Columbus, OH. This role pays $60.00-$68.00 per hour, W2, based on skill and experience level. The Data Engineer Lead plays ...

$102.10K - $122.70K/yr

Canada Job Type: Full time contract We are looking for a strong Lead Data Engineer with deep experience in Python, PySpark, SQL, and AWS to design, develop, and optimize large-scale data pipelines.

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Contract Data Engineering information

What are the key skills and qualifications needed to thrive as a Contract Data Engineer, and why are they important?

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 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 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 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:
Data engineering lead

Data engineering lead

RIT Solutions

Columbus, OH • On-site

Other

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Job description

Data Engineering Lead

Location: Columbus, Ohio - need local Onsite: 4 days a week Contract: 6 months to perm

Interview process: 1 video interview then onsite panel interview

Leads the data nimble team for their data warehouse. Focused in AWS, Glue, Athena, Step Functions, any of your AWS services. Primarily ingest files and load to the DW. Go thru framework and expose them for the data science team to use. PII, masking data, etc. Exciting project and best team in the EDW. Work with AWS toolstack and work directly with data science team. Ways to make the bank money or save bank money. They are cutting edge, any new big program runs thru their team. Pretty niche skillsets, will get to use Snowflake, Iceberg tables, all the parquet files. Any new things in data they will use. Previous exp in the knowledge stack and can come in and run. Huge demand and not enough staff to fill it. Proactive and active learners. Decent training materials there but a lot of it is on your own.