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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # BI & DATA ENGINEER - **Company:** Trilogy - **Location:** Houston, TX, United States - **Experience:** Experienced - **Salary:** $105,000 - $135,000 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, Application Programming Interfaces (APIs), Computing Platforms, Microsoft Azure, C Sharp (Programming Language), Databases, Continuous Integration, Information Engineering, Data Mining, Python (Programming Language), Microsoft Dynamics, SQL Azure, Power BI, Azure Active Directory, Standard Sql, Reverse Engineering, SQL Databases, Systems Integration, Enterprise Data Management, Automated Data Processing (ADP), Data Logging, File Transfer Protocol (FTP), Azure Data Factory, Git, Microsoft Fabric, Data Lakes, Microsoft Business Central, Restful APIs, Pagination, Software Version Control, Data Pipelines, Serverless Computing, Key Vault - **Published:** November 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eecb2f284a0cbd6e ## About the Role * 3-7 years in a data engineering, BI engineering, or hybrid analytics role * Hands-on Azure data services experience: Data Factory, Blob Storage / Data Lake, Azure SQL * Strong SQL, including performance work on large tables * Power BI: datasets, DAX measures, refresh configuration * Python or C# at a level sufficient to write and maintain API extraction code independently * Practical experience consuming REST APIs: authentication, pagination, rate limits, retry and error handling * Advanced Excel, including automation * Source control (Git) and repeatable deployment practice * Comfort working directly with business stakeholders and owning the conversation end to end * Demonstrated ownership of production systems, including responsibility when they fail Nice to Have * Experience as the sole or primary data person at a small or mid-sized company * Integration experience with Microsoft Dynamics Business Central, ADP, or Entra ID / Azure AD * Microsoft Fabric or Synapse * Regulated or compliance-driven environment - healthcare, medical waste, or finance * Waste, logistics, or field-service operations domain knowledge CI/CD or infrastructure-as-code for data pipelines ## Description The BI & Data Engineer builds and operates the systems that move data from vendor and internal source systems into Azure, and turns that data into reporting the business relies on. This is a hands-on build-and-run role on a two-person data team: you will write the extraction, build the pipeline, model the data, publish the Power BI, answer the business questions that come back, and own it when it breaks. Enterprise architecture and platform design are set by the Enterprise Data lead. You are the person who implements it - with real input into how, and real ownership of what you build. This role includes recurring reporting work that is manual today, including Excel-based reports and ad-hoc requests from finance and operations. Taking that over is part of the job, and so is systematically automating it. We are not looking for someone to maintain manual processes indefinitely; we are looking for someone who will replace them. Several of our source systems are vendor-managed platforms with limited, undocumented, or unreliable APIs. A meaningful share of this work is engineering dependable extraction from systems that were not built to be integrated with. Comfort in that environment matters more here than credentials., Reporting & Business Support * Own recurring weekly and monthly reporting cycles, including reports that are manual today * Build and maintain Power BI datasets, reports, and DAX measures * Serve as first point of contact for reporting and analytics requests from finance, operations, and leadership * Translate business questions directly into reporting without an intermediary * Systematically replace manual and Excel-based reporting with automated equivalents, and document what you replace Data Extraction & Integration * Build and maintain extraction from vendor and internal systems into Azure - REST APIs, database sources, SFTP, and file-based feeds * Engineer around real-world API constraints: missing pagination, row caps, rate limits, intermittent failures, and undocumented behavior * Implement partitioned, resumable, idempotent extraction so a failed run resumes where it stopped rather than starting over * Detect and handle silent failure modes, including truncated result sets and partial loads * Reverse-engineer undocumented vendor endpoints and maintain that documentation internally Pipelines & Data Modeling * Build, schedule, and maintain pipelines in Azure Data Factory, Azure Functions, or equivalent * Land raw source data durably before transformation so loads can be replayed without re-extraction * Build and maintain layered SQL models from raw landing through curated reporting tables, to defined architectural standards * Implement monitoring, logging, and alerting; act as first response when pipelines fail * Keep pipeline and extraction code in source control with repeatable deployment Data Quality & Reconciliation * Run reconciliation between source systems and reporting, including control totals that surface incomplete extraction * Investigate discrepancies to root cause and remediate rather than annotate * Treat unexplained variance as a defect, not a reporting caveat Security & Vendor Engagement * Follow least-privilege access practice; keep credentials and secrets in Key Vault rather than in code or configuration files * Meet compliance and audit expectations for regulated data * Reproduce and document vendor-side issues with evidence to support escalation