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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data & Integration Architect - **Company:** The Alliance - **Location:** Birmingham, AL, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Sql Data Warehouse, Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, User Authentication, Microsoft Azure, Business Systems, Databases, Data Architecture, Data Validation, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Document-Oriented Databases, Electronic Data Interchange (EDI), Information Technology Operations, JSON, Python (Programming Language), Key Management, OAuth, Data Streaming, Systems Integration, Workflow Management Systems, Data Logging, Snowflake, Boomi, Zapier, Git, Microsoft Fabric, Core Data, Operational Systems, Data Management, Api Design, Restful APIs, Webhooks, Software Version Control, Data Pipelines, Mulesoft, Custom Reports, Databricks - **Published:** November 14, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-data-integration-architect-birmingham-al--f09c25f1-7c79-4379-89de-4f36b6bc3431 ## About the Role Business Processes, Automation, Artificial Intelligence (AI), Database Extract Transform and Load (ETL), Analysis Software, Data Warehousing Software, Data Warehousing, Business Support, Building Systems, Reporting Dashboards, * 6+ years in data engineering, data architecture, or analytics engineering, including leading the design of at least one data warehouse or analytics platform * Hands-on experience building or evolving a cloud data warehouse (for example Snowflake, Microsoft Fabric, Databricks) * Working knowledge of REST APIs, webhooks, JSON, and authentication methods (OAuth, API keys), sufficient to get started with an iPaaS platform * Hands-on experience with an iPaaS or integration platform (for example Boomi, Workato, MuleSoft, Celigo, Azure Logic Apps, or similar) * Experience integrating ERP, CRM, and field-operations systems * Python or a similar language for scripting and data work * Familiarity with dbt, orchestration tools, and version control (Git) * Experience with data governance, master data management, or data quality frameworks * Experience with API-based artificial intelligence integrations * Relevant certifications (data warehousing, modeling, analytics, or iPaaS platforms) * Valid Driver’s License * Builder's mindset: comfortable doing the work, not only designing it * Business fluency: reliably connects data work to revenue, margin, utilization, and cash * Pragmatism: delivers usable increments rather than waiting for a perfect platform * Ownership: works independently with little established process * Communication: documents clearly and builds trust with business and team leaders * Ability to analyze business workflows in coordination with functional business leaders and data project team members ## Description The Senior Data and Integration Architect establishes and operates the company’s data foundation across multiple related areas: authoritative master data, data warehouses, analytics software, and inter-system data exchange and automation delivered through iPaaS and ETL platforms. Additionally, the role supports business process automation and AI-accelerated workflow design. The role is accountable for what data means, how its sources are trusted relative to one another, how it moves, and how it is consumed. It is a hands-on role with broad responsibility for design and architecture, as well as for building systems and developing custom reports and dashboards. Essential Job Responsibilities: Data Architecture and Warehouse * Define data architecture, including per-element sources of truth, intake pipelines, modeling layers, and curated reference content. * Build, configure, and operate the data warehouse, including pipeline setup, data model / view creation, and orchestration. * Establish a consistent model for core entities such as customers, locations, assets, and various financial metrics. * Establish authoritative master data for core data elements and define the trusted source system for each. * Recommends warehouse and tooling selection where platforms are not yet chosen. * Analytics platform and enablement * Stand up the BI platform and deliver core dashboards for executive, financial, and operational reporting. * Define a semantic layer with agreed definitions so that core metrics align across business functions and teams. * Support self-service analytics for business users through documentation, training, and the publishing of verified, curated datasets and data views. * Partner with finance and business leaders to translate questions and business challenges into trustworthy data solutions. Integration and Automation * Design, build, and maintain integrations and data pipelines between business systems using iPaaS and ETL platforms. * Set integration standards: API-first patterns, publish/subscribe paradigms, error handling, monitoring, logging * Automate manual, cross-system business processes in partnership with system and process owners. * Apply AI tools and techniques to accelerate workflow design and automation, with appropriate safeguards for data security and integrity. * Maintain an inventory of integrations, data flows, and dependencies. * Create a flexible process for bringing acquired companies' data into the warehouse in support of interim (pre-integration) reporting. Governance, quality, and security * Implement data quality checks and reconciliation against source systems. * Apply role-based access, secrets management, and least-privilege practices to data and integrations * Document data ownership, definitions, and retention in partnership with business stakeholders Partners and vendors * Manage relationships with platform vendors, consultants, and implementation partners. * Coordinate with Information Technology Operations on identity and infrastructure dependencies. * Track costs and make recommendations to optimize data tooling spend.