Azure BI Engineer: Data Pipelines & Power BI Lead

Trilogy Medwaste; Houston (TX); On-site; USD 110,000 - 150,000; Full time

Job summary

Trilogy MedWaste, Inc. is seeking a hands-on BI & Data Engineer to build and operate Azure-based data pipelines, model data, publish Power BI, and answer critical business questions.

You will own end-to-end data flows, from extraction to reporting, on a small two-person data team, with enterprise design guided by the Enterprise Data lead. The role includes automating manual Excel reports and handling unreliable APIs, with ownership of production systems and escalation when issues arise.

Qualifications

• 3–7 years in data/BI engineering or hybrid analytics.
• 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# to write and maintain API extraction code.
• 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.

Responsibilities

• Own recurring reporting cycles (weekly and monthly), 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.
• 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 behaviour.
• 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.
• 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.
• 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.
• 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.

Skills

3–7 years in data/BI engineering

Strong SQL

Power BI

Python or C#

REST APIs experience

Advanced Excel

Git / Source control

Stakeholder communication

Production systems ownership

Tools

Azure Data Factory

Azure Blob Storage / Data Lake

Azure SQL

Git

Job description

Trilogy MedWaste, Inc. is seeking a hands-on BI & Data Engineer to build and operate Azure-based data pipelines, model data, publish Power BI, and answer critical business questions.

You will own end-to-end data flows, from extraction to reporting, on a small two-person data team, with enterprise design guided by the Enterprise Data lead. The role includes automating manual Excel reports and handling unreliable APIs, with ownership of production systems and escalation when issues arise.