Data Engineer

Data Engineer Job ID: 2026-5593 | Type: Active - Full Time Salary Responsibilities 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. 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. Qualifications Education Bachelor's Degree in 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 education. Work Experience 3–5 years of data engineering, analytics, or related role working with production data pipelines and curated datasets. 3–5 years of experience working within a cloud‑based data or analytics platform environment, with strong SQL skills and exposure to modern data tooling. 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. Equal Opportunity Employer Ascend Federal Credit Union is an Equal Opportunity Employer. #J-18808-Ljbffr