Applied Data Engineer

MidFirst Business Credit, Inc.

Oklahoma City (OK)

On-site

USD 90,000 - 120,000

Full time

14 days+

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Job summary

MidFirst Bank is seeking a mid-level Data Engineer to design, build, and support scalable data pipelines using Microsoft Fabric and Azure to empower analytics, reporting, and enterprise decision-making. The role is hands-on and focuses on moving data from source systems into reliable, well-structured tables, views, and models for Power BI.

The ideal candidate will combine engineering fundamentals with practical Azure Fabric experiences, building ELT/ETL workflows, and collaborating with

Qualifications

  • Bachelor’s degree or equivalent practical experience.
  • 1-3 years of experience in data engineering, ETL/ELT development, or cloud data platform engineering.
  • 1-3 years of experience with Microsoft Azure data services such as Azure Data Lake, Synapse, Logic Apps, and Integration Runtime services, or closely related platform capabilities.
  • Hands-on experience building solutions in Microsoft Fabric, including Data Factory, Lakehouse, Warehouse, OneLake, notebooks, or semantic models
  • Strong SQL skills and experience with database design, data modeling, and performance tuning.
  • Experience developing data transformations using Python, Spark, SQL, or similar data engineering languages and frameworks, along with experience developing Power BI datasets, semantic models, reports, or dashboards
  • Strong understanding of dimensional modeling, medallion-style architecture, and analytics-ready data design
  • Ability to diagnose and resolve data and process issues independently.
  • Strong written and verbal communication skills with the ability to work directly with stakeholders on data requirements.

Responsibilities

  • Design, build, and maintain batch and near-real-time data pipelines using Microsoft Fabric and Azure data services.
  • Ingest data from internal and external source systems into secure, governed enterprise storage and analytics platforms.
  • Transform raw data into curated tables, views, semantic structures, and reusable data products for reporting and analytics teams.
  • Develop and optimize ELT/ETL workflows for reliability, scalability, observability, and cost efficiency.
  • Create custom data extracts and support downstream modeling, analytics, and reporting use cases.
  • Partner with business and technical stakeholders to understand data needs, define ingestion requirements, and translate them into engineered solutions.
  • Troubleshoot data quality, pipeline, schema, and process issues across the data lifecycle.
  • Implement and support data security, access controls, and governance requirements across the Azure and Fabric environment.
  • Monitor pipeline execution, investigate failures, and drive continuous improvement in performance and supportability
  • Document architecture, data flows, lineage, operational procedures, and engineering standards
  • Estimate work effort, track progress, and communicate status clearly with teammates and stakeholders.

Skills

Microsoft Fabric
Azure data services
SQL
Python
Spark
Power BI
Data modeling
ETL/ELT development
Data governance
Communication with stakeholders

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field

Tools

Azure Data Lake
Synapse
Logic Apps
Integration Runtime
Power BI datasets
Purview
OneLake
Lakehouse
Data Factory
ADLS

Job description

MidFirst Bank is seeking a mid-level Data Engineer specializing in Microsoft Fabric and Azure to design, build, and support scalable data pipelines and curated data assets for analytics, reporting, and enterprise decision-making. This role is hands-on and focused on moving data from raw source systems into reliable, well-structured tables, views, and models that support Power BI and broader business intelligence needs.

The ideal candidate combines strong engineering fundamentals with practical experience across Microsoft’s cloud data platform, including Azure and Fabric services such as OneLake, Lakehouse, Warehouse, Synapse, ADLS, Data Factory, Purview, and Power BI.

Key responsibilities

  • Design, build, and maintain batch and near-real-time data pipelines using Microsoft Fabric and Azure data services
  • Ingest data from internal and external source systems into secure, governed enterprise storage and analytics platforms
  • Transform raw data into curated tables, views, semantic structures, and reusable data products for reporting and analytics teams.
  • Develop and optimize ELT/ETL workflows for reliability, scalability, observability, and cost efficiency.
  • Create custom data extracts and support downstream modeling, analytics, and reporting use cases.
  • Partner with business and technical stakeholders to understand data needs, define ingestion requirements, and translate them into engineered solutions.
  • Troubleshoot data quality, pipeline, schema, and process issues across the data lifecycle.
  • Implement and support data security, access controls, and governance requirements across the Azure and Fabric environment.
  • Monitor pipeline execution, investigate failures, and drive continuous improvement in performance and supportability
  • Document architecture, data flows, lineage, operational procedures, and engineering standards
  • Estimate work effort, track progress, and communicate status clearly with teammates and stakeholders.

Required qualifications

  • Bachelor’s degree in computer science, engineering, information systems, or a related field, or equivalent practical experience.
  • 1-3 years of experience in data engineering, ETL/ELT development, or cloud data platform engineering.
  • 1-3 years of experience with Microsoft Azure data services such as Azure Data Lake, Synapse, Logic Apps, and Integration Runtime services, or closely related platform capabilities.
  • Hands-on experience building solutions in Microsoft Fabric, including one or more of the following: Data Factory, Lakehouse, Warehouse, OneLake, notebooks, or semantic models
  • Strong SQL skills and experience with database design, data modeling, and performance tuning.
  • Experience developing data transformations using Python, Spark, SQL, or similar data engineering languages and frameworks, along with experience developing Power BI datasets, semantic models, reports, or dashboards
  • Strong understanding of dimensional modeling, medallion-style architecture, and analytics-ready data design
  • Ability to diagnose and resolve data and process issues independently.
  • Strong written and verbal communication skills with the ability to work directly with stakeholders on data requirements.

Preferred qualifications

  • Experience supporting Power BI datasets, semantic models, and reporting solutions in an enterprise environment.
  • Experience with Azure DevOps or similar tools for version control, deployment, and release management
  • Familiarity with Purview, lineage, cataloging, and data governance practices in regulated environments.
  • Experience working in financial services, banking, or other highly governed data environments
  • Exposure to infrastructure-as-code, CI/CD pipelines, and environment promotion practices
  • Working knowledge of role-based security, sensitive data handling, and enterprise access management

Qualifications summary

This role is best suited for a hands-on individual contributor who can engineer reliable pipelines, shape data for analytics consumption, and operate effectively across Microsoft Fabric and Azure. The strongest candidates will bring practical ELT experience, solid SQL and modeling skills, sound troubleshooting ability, and a disciplined approach to security, governance, and stakeholder communication.

* Must reside within the market area to be considered.

*Position requires a minimum of 3 years of relevant US based experience.

#LI-DNI

Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws.For further information, please review the Know Your Rights notice from the Department of Labor.

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