Analytics Engineer

About the Role

Key Responsibilities

• Model & Transform - Translate user stories into data model designs, then write SQL, Python, dbt transformations that turn raw core-banking, lending, and operational feeds into governed, reusable assets (Fabric semantic models, data marts, SQL views, AS tabular models).
• Engineer with Rigor - Apply software engineering best practices such as Git branching, pull request code reviews, automated unit/integration tests, and CI/CD pipelines to guarantee every dataset is versioned, auditable, and production-ready.
• Partner & Plan - Work shoulder-to-shoulder with Data Engineers on ingestion architecture and with business stakeholders to refine acceptance criteria, ensuring models answer the right questions at the right granularity.
• Monitor & Remediate - Implement data-quality tests and real-time alerts to ensure freshness, accuracy, and uptime meet expectations; troubleshoot incidents end-to-end.
• Enable Self-Service - Coach financial, business, and operations analysts on BI tools and storytelling best practices; create workshops, playbooks, and template dashboards to raise data literacy across the bank.
• Govern & Document - Contribute to business glossaries, data dictionaries, lineage diagrams, and Purview catalogs to ensure traceability from source to report and compliance with FFIEC/FDIC standards.
• Continuously Improve - Lead retrospectives to refine delivery methodology, evaluate emerging tooling (e.g., Fabric Copilot, dbt Mesh, Data Contracts), and pursue certifications or training to stay ahead of industry trends.

Requirements

• Bachelor's in Data Analytics, MIS, Computer Science, or related field or equivalent professional experience; 3+ years delivering production data models or pipelines.
• Expertise in writing performant SQL (T-SQL or ANSI), dimensional modeling, and building semantic layers (Fabric, SSAS Tabular, or dbt).
• Experience with version control and CI/CD pipelines, including Git workflows, automated testing, and deployment via Azure DevOps, GitHub Actions, or similar tools.
• Strong Power BI skills (DAX, model optimization, role-based security) with ability to translate business questions into dashboards and reports.
• Experience with data-quality tests, lineage tools, and alerting to maintain high uptime and audit-ready pipelines.
• Exposure to cloud data platforms such as Azure Fabric, Synapse, Databricks, ADF.
• Proven ability to prioritize multiple initiatives, communicate effectively with technical and non-technical stakeholders, and thrive under tight deadlines in a regulated environment.

Nice to Have

• Familiarity with banking or FinTech data structures, payment, credit, and other financial functions.
• Proficiency in Python for data transformation, orchestration, or testing.
• Experience with workflow automation tools like Power Automate, Power Apps.
• Knowledge of REST API integration, basic .NET or JavaScript/Node for automation needs.
• Experience working in Agile/Scrum environments, story point estimation, and writing clear acceptance criteria.
• Relevant certifications such as Microsoft Fabric Analytics Engineer, dbt Certified Developer, or Azure Data Engineer.

Qualifications

• Educational background in Data Analytics, MIS, Computer Science, or related field.
• 3+ years of experience in delivering production data models or pipelines.

Benefits & Perks

• Comprehensive benefits package including Health, Financial, Retirement, and Work/Life benefits.
• Participation in an applicable annual bonus plan.