Credit Manager Jobs

About The Position

Requirements

• 8+ years of progressive experience in data engineering, analytics engineering, data architecture, data warehousing, or data platform development, including experience leading technical resources, delivery workstreams, or project teams.
• Bachelor’s degree in computer science, information systems, information technology, data management, data analytics, engineering, or a related field; significant relevant experience may be considered in lieu of a degree.
• Hands-on experience with Microsoft Fabric, OneLake, Data Factory, notebooks, lakehouse and warehouse workloads, SQL Server, and modern cloud data platforms.
• Strong knowledge of ETL/ELT design and orchestration, dimensional modeling, star and snowflake schemas, Kimball/Inmon concepts, and medallion architecture.
• Proficiency with SQL and Python, including data pipeline testing, observability, monitoring, and troubleshooting.
• Experience with Azure DevOps/Git, CI/CD practices, and modern development and deployment processes.
• Knowledge of data quality controls, metadata management, data lineage, governance, and documentation best practices.
• Experience integrating core banking, digital banking, and other operational data sources into enterprise data platforms.
• Experience working within Agile delivery environments, including ServiceNow or Jira intake, prioritization, and stakeholder communication.
• Ability to work effectively within established priorities, standards, and processes while demonstrating strong execution and follow-through.

Nice To Haves

• Relevant certifications in Microsoft Fabric, Azure, cloud data platforms, data engineering, Agile/Scrum, leadership, or project management are preferred.
• Experience partnering with or leading Data Science teams in the delivery of predictive analytics, machine learning, or AI-driven solutions.
• Familiarity with the data science lifecycle, including model development, model deployment (MLOps), monitoring, and governance.
• Experience building platforms, pipelines, and infrastructure that enable Data Scientists to develop, test, and operationalize models at scale.
• Knowledge of modern AI, machine learning, and generative AI technologies and their integration into enterprise data platforms.
• Demonstrated ability to bridge Data Engineering, Business Intelligence, and Data Science disciplines to deliver business outcomes.

Responsibilities

• Lead, coach, and develop Senior Data Engineers, including managing workload priorities, sprint commitments, performance feedback, career development, hiring, and day-to-day delivery expectations.
• Establish and maintain enterprise standards for data modeling, ETL/ELT development, orchestration, integration patterns, Microsoft Fabric/OneLake architecture, and reusable data products.
• Oversee the design, development, testing, deployment, maintenance, and optimization of data pipelines, curated data models, integrations, and data migrations across core banking, digital, operational, and analytics platforms.
• Ensure data pipelines and models are reliable, secure, performant, well-documented, and supportable through effective monitoring, data quality controls, lineage, and issue-resolution processes.
• Partner with Business Intelligence, Data Governance, Application Development, Infrastructure, vendors, and business stakeholders to translate business needs into scalable technical solutions.
• Enable trusted self-service analytics by delivering reliable, accessible, and well-governed data products that support reporting, analytics, and informed decision-making.
• Adhere to and champion our core values of curious minds, collaborative hearts, and continuous excellence.

Benefits

• weekly pay
• retirement savings options
• comprehensive health coverage including medical (with prescription)
• dental
• vision
• HSA match
• paid parental leave
• tuition reimbursement