Senior Data Engineer Biloxi 5139

JOIN THE KEESLER FEDERAL CREDIT UNION TEAM!

Keesler Federal Credit Union team members enjoy competitive salaries and a wide range of benefits, some of which include: Medical, dental, and vision insurance Section 125 Flexible Spending Accounts for Health Care and Dependent Care expenses Employee and Dependent Life Insurance 401(k) Retirement Plan with 100% match on the first 5% contributed by you Paid Leave Tuition Reimbursement and Competitive Scholarships Short-Term & Long-Term Disability Benefits Employee Assistance Program

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Position:

Senior Data Engineer Department:

Enterprise Applications Reports To:

Director of Data and Analytics FLSA:

Non-Exempt Summary:

The Senior Data Engineer is responsible for designing, building, and maintaining scalable, secure, and high-quality data pipelines that support analytics, reporting, regulatory, and operational use cases across the credit union. This role plays a critical part in enabling trusted, timely, and well-governed data while supporting enterprise initiatives such as Member 360, performance reporting, automation, and advanced analytics. This role is also responsible for enabling data foundations for AI/ML and generative AI use cases, including support for feature engineering, real-time data pipelines, and unstructured data processing.

Essential Functions:

Design, build, and maintain enterprise-grade data pipelines and integrations. Develop and optimize ETL/ELT processes for structured and semi-structured data sources. Ensure data reliability, performance, scalability, and availability. Partner with analytics and business teams to support dashboards, KPIs, and analytical use cases. Collaborate with Data Architects on data platform standards and architecture. Implement monitoring, logging, and alerting for data pipelines. Troubleshoot data quality and performance issues and perform root cause analysis. Contribute to data governance initiatives including data lineage, metadata, and access controls. Design and support data pipelines for machine learning and AI use cases, including feature engineering and model-ready datasets. Support unstructured and semi-structured data processing (e.g., text, logs) and enable capabilities such as embeddings and vector-based data retrieval where applicable. Build and maintain reliable, reusable, and well-documented data pipelines. Ingest data from core banking systems, digital platforms, and third-party vendors. Support analytics, BI, automation, and AI/ML initiatives with curated datasets. Enable data readiness for AI/ML and generative AI use cases, including support for training and inference data pipelines. Ensure adherence to data governance, security, and compliance standards. Participate in data platform modernization and cloud-based initiatives. Provide technical guidance and mentorship to junior data engineers. Serve as an escalation point for complex data issues. Participate in vendor evaluation and tool selection for data platforms. Assist with documentation of data standards and best practices. Provide backup support coverage where required.

Other Duties and Responsibilities:

Other duties as assigned.

Knowledge and Skills:

To perform this role effectively, the Senior Data Engineer must demonstrate strong technical expertise in data engineering, data integration, and analytics enablement, along with the ability to collaborate across technical and business teams.

Education:

Bachelor's degree in Computer Science, Information Systems, Engineering, or related field required.

Experience and Other Requirements:

6+ years of experience in data engineering or software engineering with a strong data focus. Proven experience building and supporting production-grade data pipelines. Strong proficiency in SQL and relational database technologies. Experience with ETL/ELT tools and data integration frameworks. Experience with modern data platforms (e.g., Databricks, cloud-based analytics). Familiarity with data modeling techniques and analytics-ready datasets. Experience working within SDLC, CI/CD, and version control frameworks. Understanding of data security, governance, and regulatory requirements. Familiarity with data patterns supporting AI/ML, such as feature stores, real-time/event-driven pipelines, or vector databases. Experience in a credit union or financial institution. Familiarity with core and digital banking platforms such as Symitar, Alkami, MeridianLink, or similar. Experience with cloud data platforms such as Fabric or Snowflake. Experience supporting Power BI or similar BI tools. Experience supporting AI/ML or generative AI use cases, including preparation of training data, feature engineering, or working with unstructured data.

Interpersonal Skills:

Must possess strong interpersonal and collaboration skills, with the ability to work effectively across technical and business teams. Demonstrates professionalism, integrity, and accountability.

Computer Skills:

(See Essential Functions, Education, and Experience Requirements above)

Certificates, Licenses and Registrations:

Professional certifications in data engineering, cloud platforms, or analytics are preferred.

Physical Demands:

The physical demands described here are representative of those that must be met by an individual to successfully perform the essential functions of this job. Reasonable accommodations may be made.

Work Environment:

Extensive use of desktop computer is required. The noise level is that of a normal office environment. When working in secured areas, elevated noise levels may be present.

Declaration:

The human resources department retains the sole rights and discretion to update this job description. #HPIND