Senior Data Engineer – Microsoft Fabric Platform

2020companies

Southlake (TX)

On-site

USD 120,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Competitive salary

Daily Pay

Health/Dental/Vision

401K with matching

Paid Time Off

Paid Holidays

Scholarship opportunities

Employee Assistance Program

Leadership Development Program

Job summary

2020 Companies is hiring a Senior Data Engineer to build and scale a client-facing analytics platform that directly drives revenue and executive decision-making. You will design and implement Microsoft Fabric pipelines, lakehouse models, and optimize Power BI performance for fast, reliable insights.

This role is highly visible and impact-driven, with direct influence on client satisfaction, retention, and growth.

Qualifications

5-8 years of data engineering experience.
Strong SQL, data modeling, and hands-on Delta Lake experience.
Microsoft Fabric experience – you’ve built it, not just read about it.
Dimensional modeling you can defend in a design review.
Power BI semantic model optimization expertise.
A track record of building scalable ingestion frameworks.
A track record in client-facing or revenue-driven analytics environments.
Uses critical thinking to break down ambiguous problems, evaluates tradeoffs, and makes sound, data-informed decisions.
Strong leadership and communication skills, written and verbal.
Experience working in agile environments with CI/CD.

Responsibilities

Design scalable data systems across pipelines, lakehouse, and semantic layers.
Develop ingestion frameworks for monitoring, observability, scalability, and reuse.
Make architectural decisions balancing cost, SLA, and scale while avoiding debt.
Build and maintain Microsoft Fabric pipelines and notebooks supporting analytics and reporting.
Ensure data accuracy, timeliness, reliability, and trust for stakeholders.
Optimize refresh strategies and reduce compute spikes.
Lead data modeling standards for multi-client scalability.
Defend modeling decisions in design reviews and ensure reuse across the platform.
Champion SDLC practices (Git, CI/CD, testing) and enforce engineering standards.
Improve development workflows and team efficiency; deliver iteratively in small batches.