Senior Data Analyst Engineer

Woodforest Acceptance Solutions; The Woodlands (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Woodforest Acceptance Solutions is seeking a Senior Data Engineer & Analyst to design, build, and optimize data platforms powering our Data‑as‑a‑Service (DaaS) offerings. You will architect scalable pipelines, shape data models, deliver high‑quality datasets to customers, and generate insights to drive product and business decisions across internal and external clients.

This hands‑on role requires deep Azure expertise (Data Lake, Data Factory, Synapse, Cosmos DB) and strong SQL, Python, and data

Qualifications

• 5+ years of experience in data analysis, analytics, or business intelligence roles.
• Experience in fintech, payments, banking, or financial services.
• Bachelor’s degree or equivalent experience in a relevant field.

Responsibilities

• Architect and optimize data models, storage layers, and compute patterns for both operational and analytical workloads.
• Work with third party data engineering team to ensure optimal performance of data infrastructure.
• Implement robust data quality, validation, and monitoring frameworks.
• Ensure data systems meet high standards for scalability, reliability, and security.
• Manage change related to the data environment.
• Perform exploratory data analysis and build analytical datasets to support product development and business decision-making.
• Use Wisdom.ai and other analytical tools to generate insights, build dashboards, and support advanced analytics use cases.
• Partner with product, engineering, and business teams to translate ambiguous questions into clear analytical outputs.
• Contribute to the design and delivery of internal and external DaaS products, including data APIs, curated datasets, and automated reporting solutions.
• Define SLAs, data contracts, and quality standards for delivered datasets.
• Collaborate with product managers to prioritize features, define requirements, and ensure customer needs are met.
• Support customer onboarding, troubleshooting, and optimization of data delivery workflows.

Skills

Azure data technologies

SQL

Python

Data governance

Mentoring/leadership

Education

Bachelor's degree in Analytics, Statistics, Mathematics, CS, Economics, or related field

Tools

Azure Data Factory

Azure Data Lake

Cosmos DB

Synapse Analytics

Wisdom.ai

Job description

We are seeking a Senior Data Engineer & Analyst to design, build, and optimize the data platforms that power our internal and external Data‑as‑a‑Service (DaaS) offerings. This role blends deep engineering expertise with strong analytical capability. You will be responsible for architecting scalable data pipelines, shape data models, deliver high‑quality datasets to customers, and generate insights that drive product and business decisions. You will work across the full data lifecycle—from ingestion and transformation to analytics, governance, and productization—using a modern Azure‑based stack including Azure Data Lake, Azure Data Factory, Cosmos DB, Synapse Analytics, and Wisdom.ai.This is a hands‑on role for someone who thrives in a fast‑moving environment, enjoys solving complex data problems, and wants to influence the direction of data products used across the organization and by external clients.

Key Responsibilities:

Data Engineering & Architecture

• Architect and optimize data models, storage layers, and compute patterns for both operational and analytical workloads.
• Work with third party data engineering team to ensure optimal performance of data infrastructure
• Implement robust data quality, validation, and monitoring frameworks.
• Ensure data systems meet high standards for scalability, reliability, and security.
• Manage change related to the data environment.

Analytics & Insight Generation

• Perform exploratory data analysis and build analytical datasets to support product development and business decision‑making.
• Use Wisdom.ai and other analytical tools to generate insights, build dashboards, and support advanced analytics use cases.
• Partner with product, engineering, and business teams to translate ambiguous questions into clear analytical outputs.
• Contribute to the design and delivery of internal and external DaaS products, including data APIs, curated datasets, and automated reporting solutions.
• Define SLAs, data contracts, and quality standards for delivered datasets.
• Collaborate with product managers to prioritize features, define requirements, and ensure customer needs are met.
• Support customer onboarding, troubleshooting, and optimization of data delivery workflows.

Technical Leadership

• Serve as a subject‑matter expert on Azure data technologies, modern data architecture, and best practices.
• Mentor junior engineers and analysts, providing guidance on design patterns, coding standards, and analytical approaches.
• Drive continuous improvement across the data platform, including automation, observability, and performance enhancements.
• Experience with API‑based data delivery and microservices architectures.
• Background in machine learning pipelines or AI‑assisted analytics.
• Experience working in product‑oriented or customer‑facing data roles.
• Familiarity with credit payments related data.
• Deep expertise with Azure data services (Data Factory, Data Lake, Synapse, Functions, Key Vault, etc.).
• Strong hands‑on experience with Cosmos DB and distributed NoSQL data modeling.
• Proficiency in SQL, Python, and modern data transformation frameworks.
• Experience designing and delivering data products or DaaS solutions.
• Strong analytical skills with the ability to interpret complex datasets and communicate insights clearly.
• Familiarity with Wisdom.ai or similar AI‑driven analytics platforms.
• Solid understanding of data governance, security, and compliance best practices.

Minimum Qualifications/Experience:

• 5+ years of experience in data analysis, analytics, or business intelligence roles.
• Experience in fintech, payments, banking, or financial services.

Formal Education & Certification:

• Bachelor’s degree in Analytics, Statistics, Mathematics, Computer Science, Economics, or a related field (or equivalent experience).