Applied Data Engineer

MidFirst Bank•Oklahoma City, OK

11h•Onsite

About The Position

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, Synapse, ADLS, Data Factory, Purview, and Power BI.

Requirements

Bachelor’s degree in computer science, engineering, information systems, or a related field, or equivalent practical experience.
3+ years of experience in data engineering, ETL/ELT development, or cloud data platform engineering.
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.

Nice To Haves

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

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.