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Airflow Engineer Jobs in Ohio (NOW HIRING)

Senior Data Engineer

Cleveland, OH · On-site

$102K - $139K/yr

SENIOR DATA ENGINEER We are looking for a highly skilled and strategic Senior Data Engineer to lead ... Deep production experience with dbt for data modeling and Airflow for orchestration. * Advanced ...

Engineering Manager, DevOps

Columbus, OH · On-site +1

$51 - $69.75/hr

Partner hand-in-hand with Product Engineering Teams, our Data Team (Airflow, Snowflake, dbt), and ... other stakeholders to align roadmaps and unlock velocity. * Contribute hands-on by writing ...

AI Software/ Data Engineer

Cincinnati, OH · On-site

$111K - $134K/yr

They are seeking a versatile AI Software Engineer to bridge AI initiatives with production ... Airflow, Kafka, or cloud-native serverless functions. Company : Vurvey Labs is an applied AI ...

Engineer

Cleveland, OH · On-site

$100K - $120K/yr

Skill: Sr Data Engineering Architect Fraud Domain Must Have Technical/Functional Skills: * Define ... Hands-on experience with SQL, Python, Spark/PySpark, Databricks, Kafka, Airflow, Snowflake, and ...

Senior Data Engineer

Columbus, OH · On-site

$142K - $177K/yr

Expert proficiency in SQL and Python, with deep experience in Airflow or a comparable orchestrator ... Experience mentoring engineers and contributing to team standards and culture * Ability to navigate ...

Senior Data Engineer

Columbus, OH · On-site +1

$177K/yr

Expert proficiency in SQL and Python, with deep experience in Airflow or a comparable orchestrator ... Experience mentoring engineers and contributing to team standards and culture * Ability to navigate ...

Senior Data Engineer

Columbus, OH · On-site

$142K - $177K/yr

Expert proficiency in SQL and Python, with deep experience in Airflow or a comparable orchestrator ... Experience mentoring engineers and contributing to team standards and culture * Ability to navigate ...

Perform load calculations, airflow analysis, and equipment sizing using industry-standard software * Create detailed engineering drawings, schematics, and specifications using CAD tools * Collaborate ...

Showing results 21-40

Airflow Engineer information

What is the difference between Airflow Engineer vs Data Engineer?

AspectAirflow EngineerData Engineer
CredentialsOften requires knowledge of Python, SQL, and cloud platformsRequires similar skills plus database management and ETL experience
Work EnvironmentFocuses on designing and maintaining workflows in data pipelinesBuilds and manages data infrastructure and pipelines
Industry UsageCommon in data-driven companies, analytics teams, and cloud servicesUsed across industries for data integration, storage, and processing

While both roles involve data workflows, an Airflow Engineer specializes in creating and managing workflows using Apache Airflow, whereas a Data Engineer handles broader data infrastructure and pipeline development. The roles often overlap, but the Airflow Engineer focuses more on workflow orchestration within the data ecosystem.

Senior Data Engineer

Further

Cleveland, OH • On-site

$102K - $139K/yr

Full-time

Re-posted 12 days ago


Job description

WE'RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.
Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients. If this sounds exciting to you, let's chat!
SENIOR DATA ENGINEER
We are looking for a highly skilled and strategic Senior Data Engineer to lead in our data engineering consulting team. In this role, you will serve as the technical cornerstone for our clients, designing and deploying the sophisticated data architectures required to support production-grade Artificial Intelligence and Machine Learning applications. This is a high-impact role where you will set the standards for data quality, modeling, and orchestration across the organization. You will navigate diverse technical environments, and your work will directly enable the transition from experimental AI prototypes to resilient, enterprise-scale systems that deliver measurable business value.
What experience should you have:
  • 6+ years of data engineering experience with a focus on modern cloud platforms.
  • Expert-level proficiency in Python and SQL is mandatory.
  • Strong software engineering background with proficiency in Python for building custom integrations and data tools.
  • Deep production experience with dbt for data modeling and Airflow for orchestration.
  • Advanced knowledge of cloud-native data suites within GCP (preferred), AWS, or Azure.
  • Proficiency in managing environment reproducibility using Terraform and Docker, ensuring pipelines are CI/CD compliant.
  • Expert knowledge of cloud data warehouses (BigQuery or Snowflake) and their internal architecture.
  • Experience with AI workflows and data systems like vector databases, PostgreSQL, Vertex AI, Pub/Sub.

Preferred Qualifications
  • Experience architecting feature stores or data pipelines specifically for ML workloads.
  • The ability to navigate diverse technical environments and corporate cultures while maintaining a high standard of delivery and client satisfaction.
  • A commitment to software engineering best practices, including version control, unit testing, and comprehensive documentation.
  • An analytical thinker who anticipates scaling bottlenecks and security vulnerabilities before they impact production.

What you'll be doing in this role:
  • Architect and build scalable, high-volume ELT/ETL pipelines that ingest complex data sets from diverse client systems, including legacy on-premise databases, ERPs, and third-party APIs, into centralized cloud warehouses.
  • Lead the audit and optimization of existing data workflows, refactoring inefficient queries and data models to significantly reduce latency and operational costs for enterprise-scale environments.
  • Design and implement comprehensive data quality frameworks, ensuring automated testing and validation logic catches anomalies before they reach production models or executive dashboards.
  • Design and implement data pipelines specifically for AI workloads, including the management of vector databases to support Retrieval-Augmented Generation (RAG) and model inference.

What you'll need to accomplish in your first year:
  • Own the roadmap for data platform stability and scalability enhancements, ensuring the infrastructure can support the evolving needs of both corporate IT and AI research teams.
  • Provide technical mentorship to the engineering team, conducting rigorous code reviews and driving improvements in coding standards, documentation, and system reliability.
  • Standardize the organization's approach to the Modern Data Stack (MDS), driving the adoption of best practices in dbt, Airflow (Cloud Composer), and Beam (Dataflow) across diverse client engagements.

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.
Apply today or check out all our opportunities!
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