Data Engineer

Ascend is the largest credit union in Middle Tennessee and one of the largest credit unions in the United States, with over $4 billion in assets. With an occupation-based field of membership, Ascend is focused on the expansion and diversification of the select employee groups it serves, which creates greater security for the credit union and its member-owners. Approximately 650 employees serve more than 250,000 members from 28 Middle Tennessee branch locations, Regional Operations Center, Teller Center and Corporate Headquarters. Ascend recognizes that its employees are critical to the credit union’s sustained success and future growth. Our employees are the face of the credit union and their personal successes fuel the success of the team. Through collaboration between employees, management, our membership and our Board, we fuel an engine that propels the credit union forward.

Thank you for your interest in a career with Ascend Federal Credit Union! Being employed by Ascend is vastly different than just holding a job. The credit union prides itself on providing employees rewarding career opportunities, competitive benefits and a unique work culture. The credit union’s commitment to its employees is fostered by its commitment to the member-owners, ensuring dedicated and engaged employees to serve the membership. Ascend’s vision to be the most loved credit union in our market by employees and members alike has earned the credit union distinctions including Federal Credit Union of the Year (NAFCU, 2015), Best Credit Union to Work For (2016-2025) and Training MVP Awards (2015-2026).

This role is a key contributor to the enterprise data platform, responsible for building, maintaining, and enhancing data pipelines and curated data assets that support analytics, reporting, and advanced data use cases. The position focuses on executing well‑defined data platform work within established architecture, standards, and patterns. Work is hands‑on across ingestion, transformation, and modeling layers, translating data requirements into reliable, production‑ready solutions. The role partners closely with engineering, modeling, analytics, and platform stakeholders, and operates independently on scoped work while collaborating with senior technical leadership for guidance and alignment on standards. This position is well suited for someone who enjoys building and operating data pipelines, deploying changes to production, and contributing to a modern cloud‑based analytics platform. #LI-KB1

• Work with technical and nontechnical partners to understand data requirements and translate them into well-defined data engineering tasks and deliverables.
• Build, maintain, and enhance data pipelines and transformations on the enterprise analytics platform, following established platform architecture, standards, and engineering patterns.
• Maintain and enhance existing production data pipelines, including troubleshooting data issues, pipeline failures, and performance concerns.
• Develop and maintain data transformations with a focus on data quality, scalability, and long-term maintainability.
• Write, optimize, and maintain SQL based data logic to support ingestion, transformation, validation, and analytical use cases.
• Implement data quality checks and validation mechanisms to ensure consistency and reliability of curated datasets.
• Deploy changes to production environments using established CI/CD processes and platform standards.
• Follow defined data governance, security, and operational practices when building and maintaining data solutions.
• Work within an Agile delivery model, participating in planning, refinement, and team ceremonies.
• Collaborate closely with engineering, modeling, analytics, and platform stakeholders to support evolving data platform needs.
• Provide occasional after hours or off schedule support when required to address data platform issues.
• Perform other duties as required or assigned.

Education

• Bachelor's Degree Information Systems, Data Engineering, Data Science, or a related field is required or
• Equivalent professional experience in production data environments will be considered in lieu of formal educational requirements.

Work Experience

• 3-5 years Data engineering, analytics, or related role working with production data pipelines and curated datasets is required and
• 3-5 years Experience working within a cloud‑based data or analytics platform environment, with strong SQL skills and exposure to modern data tooling is required

Knowledge, Skills, and Abilities

• Working knowledge of modern data engineering concepts, including data ingestion, transformation, and curation across layered data architectures.
• Strong SQL skills, with demonstrated experience writing, optimizing, and maintaining queries and data transformations in production environments.
• Hands on experience building and maintaining data pipelines on Microsoft Fabric or a comparable cloud analytics platform, following established patterns and standards.
• Practical experience with ELT/ETL workflows and transformation frameworks (e.g., dbt or similar tools), with attention to data quality, maintainability, and performance.
• Familiarity with CI/CD concepts and version controlled deployment processes for data pipelines and analytics assets (e.g., pull requests, automated deployments).
• Experience working with relational source systems (e.g., SQL Server or equivalent) and integrating data from multiple upstream sources.
• Exposure to data quality validation techniques, including basic checks, reconciliations, and anomaly detection.
• General familiarity with the Microsoft analytics ecosystem, including cloud based data storage, processing, and analytics services.
• Basic understanding of data governance, security, and privacy concepts, with the ability to follow defined policies and operational standards.
• Exposure to scripting or programming languages (e.g., Python) for data processing or pipeline support is preferred but not required.
• Ability to work independently on well-defined tasks while knowing when to seek guidance or clarification.
• Strong problem-solving skills, with the ability to troubleshoot data issues and contribute to Root cause analysis.
• Effective written and verbal communication skills, with the ability to collaborate productively across engineering, analytics, and platform teams.
• Comfortable working in an Agile environment with evolving priorities and iterative delivery.
• Strong attention to detail, a sense of ownership over work delivered, and a focus on building reliable, production ready data solutions.
• Regular and reliable attendance is required.

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Ascend Federal Credit Union is an Equal Opportunity Employer.