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Azure Data Engineer

Spar Information SystemsFrisco, TX🇺🇸United StatesPosted 24 Aug 2026

Why This Role Stands Out

Advance your career as a Senior Azure Data Engineer at Spar Information Systems, where you'll design and build scalable data pipelines for T-Mobile's finance platforms using cutting-edge cloud technologies. This role is perfect for experienced engineers with strong SQL/Python skills and a passion for data architecture who are eager to mentor others and drive best practices within a dynamic team. Take advantage of this long-term contract opportunity to make a significant impact.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Frisco, TX, United States
Posted
2 weeks ago
SQLScalaAzureDatabricksPower BIPython

Job Description

Hello Everyone,

Hope you are doing good!!!!

My name is Pavan and I work with SPAR Information System., I have a great opportunity for you, please find the job details below, if you are interested in applying please send me your updated resume and best time for you to discuss about this opportunity in details.

Role: Data Engineer

Location: Bellevue, WA/ Frisco, TX Hybrid work role

Duration: Long term contract

ABOUT THE ROLE
Our team builds and maintains data products within the Care & Retail domain, delivering reliable, scalable solutions that power easy & actionable insights across Consumer reporting. We support performance management, operational visibility, and business decision-making for millions of customers across Magenta & Metro.
We're looking for engineers who operate as product owners. You'll build things that last, improve what exists, and adopt the best available tools, including AI, to do it more effectively. If you think in systems and take end-to-end accountability, you'll fit here.
WHAT YOU'LL DO
Design, build, and optimize data pipelines and structures that support reliable, efficient data processing & delivery at scale
Contribute to a growing semantic & analytics layer, including dimensional modeling for Care & Retail reporting
Migrate and modernize pipelines to standardized, reusable ingestion patterns and layered data architecture
Engage business teams to understand their problem space and coordinate technical changes end-to-end
Perform impact analysis, diagnose issues, and validate that changes deliver expected outcomes
Conduct root cause analysis on data and process issues, and flex into ad hoc analysis when the business needs answers fast
Identify opportunities to consolidate redundant data objects, reduce support burden, and improve reusability
Adopt and apply AI tools and modern engineering practices to improve throughput and reduce per-unit delivery overhead
WHAT WE'RE LOOKING FOR
Experience
2-4 years of data engineering experience
Experience designing & building data pipelines and data lakes in a cloud environment
Experience with root cause analysis on data and process issues, with the ability to trace problems across systems and translate findings into action
Comfortable flexing into an analytical or systems analyst role when the work requires it - this team supports the business, not just the pipeline
Experience managing stakeholder expectations across technical & business teams
Technical Skills
Strong SQL, including performance tuning & optimization in large-scale analytical environments (Required)
Familiarity with Microsoft Fabric, Databricks, and the Azure data stack, including Azure Data Lake Storage (Preferred)
Familiarity with dimensional modeling, star schema design, and semantic layer concepts (Preferred)
Familiarity with medallion architecture (bronze/silver/gold) and data lake design patterns (Preferred)
Familiarity with Power BI for understanding downstream analytics consumption; DAX experience a plus (Preferred)
Familiarity with Python, Scala, or other scripting languages used in pipeline development (Preferred)
Familiarity with common software design principles such as DRY, SRP, and OOP (Preferred)
Experience using AI tools, agents, or automation to accelerate engineering workflows (Preferred)
How You Work
Systems thinker: you consider how data, tools, processes, and stakeholders interact across a broader ecosystem
Product owner mindset: end-to-end accountability for what you build, not just the ticket in front of you
Clear communicator: you can explain technical tradeoffs to non-technical partners without losing the substance
Bias toward simplicity: you ask whether complexity is necessary before adding it
EDUCATION
Bachelor's degree plus 2+ years of related work experience, or a combination of education & experience deemed equivalent
Relevant fields include Computer Science, Statistics, Informatics, Information Systems, or a quantitative equivalent

Thanks & Regards,

Pavan Raikhelkar

LEAD TALENT ACQUISITION SPECIALIST

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