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Data Optimisation Jobs in Ohio (NOW HIRING)

The Data Sherpas

Data Architect

Mentor, OH · On-site

$57 - $73.25/hr

Strong production experience designing and optimizing Snowflake environments (SnowSQL, data sharing, schema design) • Advanced Data Mapping Skills: Demonstrated success leading extensive source-to ...

ChoiceLocal

SEO & AEO Strategist

Westlake, OH · On-site

Develop and present data-driven recommendations to improve results * Align optimization priorities with conversion and business outcome goals Content & AI Visibility Strategy * Guide content ...

AMEND Consulting

Data Engineer

Cincinnati, OH · On-site

$111.70K - $134.20K/yr

Responsibilities : • Create and maintain optimal data pipeline architecture • Assemble large, complex data sets that meet functional / non-functional business requirements • Identify, design ...

AMEND Consulting

Data Scientist

Cincinnati, OH · On-site

Responsibilities : • Build scalable, data-driven tools and analytics solutions that address real client challenges. • Apply optimization, forecasting, machine learning, and predictive analytics ...

AMEND Consulting

Data Engineer

Cincinnati, OH · On-site

$109.90K - $131.90K/yr

Create and maintain optimal data pipeline architecture * Assemble large, complex data sets that meet functional / non-functional business requirements * Identify, design, and implement internal ...

AMEND Consulting

Data Engineer

Cincinnati, OH · On-site

$109.90K - $131.90K/yr

Create and maintain optimal data pipeline architecture * Assemble large, complex data sets that meet functional / non-functional business requirements * Identify, design, and implement internal ...

IRIS Software, Inc.

$102.10K - $122.70K/yr

Proficiency in Python and SQL for building and optimizing ETL/ELT pipelines. * Experience with data warehousing, data modeling, and large-scale data processing. * Hands-on experience with ...

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Data Optimisation information

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

To thrive as a Data Optimisation Specialist, you need strong analytical skills, proficiency in data analysis, and a background in statistics or computer science, often supported by relevant degrees or certifications. Familiarity with data management tools like SQL, Python, Excel, and optimisation platforms such as Google Analytics or Tableau is typically required. Excellent problem-solving abilities, attention to detail, and effective communication are essential soft skills for translating insights into actionable strategies. These skills ensure that data-driven decisions are accurate, impactful, and aligned with business objectives.

What are the most common challenges faced in a Data Optimisation role, and how can I prepare for them?

One of the main challenges in a Data Optimisation role is dealing with large, complex datasets that may have inconsistencies or missing information. You’ll often need to balance improving data quality with maintaining data integrity and system performance. Collaborating across departments, such as IT, analytics, and business operations, is typical, so strong communication skills are essential. Preparing by learning best practices in data cleaning, ETL processes, and familiarizing yourself with relevant tools will help you succeed and adapt quickly.

What is data optimisation?

Data optimisation refers to the process of improving the quality, accessibility, and efficiency of data within an organization. It involves cleaning, structuring, and organizing data so that it can be used more effectively for analysis, decision-making, and business operations. Data optimisation can help reduce storage costs, enhance system performance, and ensure that accurate and relevant data is available when needed. This process often includes data deduplication, compression, and the implementation of best practices for data management.

What is the difference between Data Optimisation vs Data Analysis?

AspectData OptimisationData Analysis
Primary FocusImproving data processes and system efficiencyInterpreting data to uncover insights
Skills RequiredData management, process improvement, technical skillsStatistical analysis, reporting, critical thinking
Work EnvironmentIT teams, data engineering, system optimizationBusiness units, research teams, analytics departments
CertificationsData management, database certificationsData analysis, statistical certifications

Data Optimisation focuses on enhancing data systems and processes for efficiency, while Data Analysis involves examining data to generate insights. Both roles require strong technical skills, but their objectives differ: one improves data infrastructure, the other interprets data for decision-making.

What are popular job titles related to Data Optimisation jobs in Ohio? For Data Optimisation jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Data Optimisation jobs in Ohio look for? The top searched job categories for Data Optimisation jobs in Ohio are:
Data Optimisation jobs near you
Infographic showing various Data Optimisation job openings in Ohio as of May 2026, with employment types broken down into 1% Full Time, 98% Part Time, and 1% Nights. Highlights an 97% Physical, and 3% Hybrid job distribution.
Data Architect Senior or Data Architect Lead

Data Architect Senior or Data Architect Lead

Federal Reserve Bank of Cleveland

Cleveland, OH • On-site

$65 - $87.25/hr

Full-time

Posted 23 days ago

Job description

Job Summary:
Federal Reserve Bank of Cleveland is committed to fostering the stability and efficiency of the nation's financial systems. They are seeking a Senior Data Architect or Data Architect Lead to lead design and architecture decisions for complex product development initiatives, focusing on modernizing data analytics assets and transitioning to cloud-native designs.
Responsibilities:
• Accountable for selecting design patterns, technologies, and solution architectures for product development projects by analyzing business, technical, and enterprise requirements to ensure alignment with organizational objectives and industry best practices.
• Engages with business areas, clients, and stakeholders as a trusted consultant to identify gaps, present solution options, and recommend optimal technologies; documents architecture decisions and technical standards to support knowledge sharing.
• Champions complex, strategic enterprise solutions by communicating architecture decisions and technical concepts effectively across all organizational levels, from technical teams to senior management.
• Refines and supports a portfolio-wide data optimization strategy to further align existing assets to the new, cloud-native architecture.
• Collaborates with cross-functional teams throughout the full development lifecycle, including ideation, development, integration, testing, and production support.
• Researches and evaluates emerging technologies and industry trends; develops strategic recommendations for architecture investments that reduce cost, increase security, eliminate redundancies, and improve system flexibility.
• Builds and maintains strategic relationships with key technology vendors and business partners to stay current on industry developments and enterprise architecture landscape shifts.
• Owns the data infrastructure strategy and roadmap; assesses current state, identifies gaps, and drives architectural initiatives and monitoring solutions from planning through implementation.
• Establishes, enforces, and evolves data governance policies, quality frameworks, and compliance practices to ensure data integrity, security, accuracy, and regulatory adherence across critical systems.
• Collaborates with data stewards, compliance teams, and technical leads to translate governance and regulatory requirements into technical controls, validation rules, access policies, and audit mechanisms.
• Assists in establishing a flexible and valuable portfolio-level data catalog that will drive transparency and promote reusability.
Qualifications:
Required:
• Candidates must be a U.S. citizen.
• Bachelor’s degree and 5 years of professional work experience or Master’s degree and 3 years of professional work experience for Data Architect Senior.
• Bachelor’s degree and 7 years of related work experience or Master’s degree and 5 years of related work experience for Data Architect Lead.
• Proven track record of designing and implementing complex, production-grade systems.
• Experience working in collaborative, cross-functional environments.
• Deep experience designing distributed systems, microservices, API architectures, and cloud-native applications.
• Understanding of payment systems, regulatory requirements, and banking technology landscape.
• Expertise in web, mobile, and backend architectures with strong grasp of scalability, security, and performance patterns.
• Hands-on experience with cloud platforms (e.g., AWS), containerization, CI/CD (e.g., GitLab), and infrastructure-as-code (e.g., CDK or Terraform).
• Proficiency in data modeling, integration patterns, and database technologies (relational and NoSQL).
• Working knowledge of TOGAF, C4, AWS Well-Architected Framework or similar architecture analysis and documentation approaches.
Company:
The Federal Reserve Bank of Cleveland was established in 1914 as a part of the Federal Reserve System Founded in 1914, the company is headquartered in Cleveland, USA, with a team of 501-1000 employees. The company is currently Late Stage.

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