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Ai Data Developer Jobs in Ohio (NOW HIRING)

Lexisnexis Risk Solutions

AI Data Analyst

Dayton, OH

The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own endtoend data pipelines and is ...

RELX

AI Data Analyst

Dayton, OH · On-site

The AI Data Analyst partners with data engineering, AI, and governance teams to assess data readiness, identify gaps and recommend improvements. This role does not own endtoend data pipelines and is ...

Deloitte

Databricks Data Engineer II

Columbus, OH

$110K - $132K/yr

Join Deloitte's Core AI & Data practice and help organizations modernize data platforms, strengthen ... As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based ...

Deloitte

Databricks Data Engineer II

Cleveland, OH

$111K - $133K/yr

Join Deloitte's Core AI & Data practice and help organizations modernize data platforms, strengthen ... As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based ...

Deloitte

Databricks Data Engineer II

Cincinnati, OH

$109K - $131K/yr

Join Deloitte's Core AI & Data practice and help organizations modernize data platforms, strengthen ... As a Databricks Data Engineer, you will support the design, build, and optimization of cloud-based ...

Deloitte

Agentic AI, AI & Data Science Engineer

Cleveland, OH · On-site

$111K - $133K/yr

Amazon Q Business & Q Developer (enterprise AI assistant and code generation capabilities); Cognito ... BigQuery (for data processing and analytics); Cloud Run, Cloud Functions, and GKE (for agent ...

The Hartford

Director, Data Architect

Columbus, OH · Hybrid

$61.50 - $79.25/hr

AI Data Engineering leader responsible for Implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions. * Real-Time Data ...

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Ai Data Developer information

What is the difference between Ai Data Developer vs Data Scientist?

AspectAi Data DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of AI frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops AI models, integrates AI solutions into applicationsAnalyzes data, builds predictive models, interprets data trends
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles involve working with data and AI, Ai Data Developers focus on creating and deploying AI models within applications, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap but differ mainly in their primary focus and application environment.

What are popular job titles related to Ai Data Developer jobs in Ohio? For Ai Data Developer jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Ai Data Developer jobs in Ohio look for? The top searched job categories for Ai Data Developer jobs in Ohio are:
What cities in Ohio are hiring for Ai Data Developer jobs? Cities in Ohio with the most Ai Data Developer job openings:
Ai Data Developer jobs near you
Staff AI Data Engineer

Staff AI Data Engineer

Park Place Technologies

Highland Heights, OH • On-site

$111K - $133K/yr

Full-time

Posted 18 days ago

Park Place Technologies rating

7.6

Company rating: 7.6 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

92nd of 210 rated it services

Job description

Department: AI Data Engineering

Reports To: Data Engineering Team Lead / Engineering Manager

Position Overview:

Midlevel engineer who designs and maintains scalable data pipelines, ETL processes and data platforms to support AI/ML workloads, integrating vector stores and ensuring data quality and compliance.

Key Responsibilities:

  • Implement and maintain scalable batch and streaming data pipelines to ingest, transform and serve data for AI/ML workloads; work with senior engineers and architects on designing pipelines and processes.
  • Develop ETL/ELT processes using Python and SQL to prepare training, test, and production datasets and feature stores. Experience with big data technologies (Spark, Hadoop) and flow tools (Kafka, NiFi) is a plus but not required.
  • Build and maintain data warehouses and lakes; integrate with vector stores to support retrievalaugmented generation (RAG) systems. aPartner with more senior engineers to collaborate with AI Data Engineering, IT Data Engineering, Infrastructure, AI Engineering, Security and Business Leaders to deliver features for model training and inference
  • Implement data validation and quality checks with validation from more senior engineers; maintain documentation of data flows and schemas.
  • Work with more senior engineers to ensure pipelines meet data quality, observability, security and regulatory compliance standards.
  • Work with Model Context Protocol (MCP) to integrate into data pipelines and make modifications to existing MCP connections with guidance from more senior engineers.

Qualifications:

  • At least two (2) years’ experience working in a Data Engineering, Data Science, Software Development or other relevant role.
  • Professional experience with programming in either Python or an object-oriented programming language.
  • Strong knowledge of relational and NoSQL-based databases, with significant proficiency in SQL.
  • Understanding of ETL processes and data modeling concepts.
  • Exposure to data processing frameworks and tools (examples are but not all required as Apache Spark, Kafka, dlt, dbt), and cloud data services (AWS Glue, Azure Data Factory, GCP Dataflow). Experience with one or more of these tools or services is a plus but not required.
  • Knowledge of data warehousing, lakehouse architectures, and data modeling concepts. Experience with ML tools such as pytorch is a plus.
  • Understanding of machinelearning workflows and ability to build feature stores for AI models.
  • Exposure to containerization (Docker), Kubernetes and continuous integration/continuous deployment (CI/CD). Experience is a plus but not required.
  • General understanding of AI/ML concepts with the ability and willingness to learn more.
  • Ability to collaborate with team leadership and Data Engineering, Infrastructure, AI Engineering, Security and Business peers.
  • Strong problemsolving, communication and teamwork skills.

What Park Place Technologies employees say

Pay

Hours and flexibility

Workplace

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