More jobs:
Data Engineer
Job in
Phoenix, Maricopa County, Arizona, 85001, USA
Listed on 2026-10-30
Listing for:
Virtues R & D
Full Time
position Listed on 2026-10-30
Job specializations:
-
Software Development
Data Engineering, SQL Developer
Job Description & How to Apply Below
Data Engineer:
Microsoft Fabric, Batch and Streaming Pipelines
Experience: 5+ years (adjust to the client's level) |
Hours: Full-time, 40 hrs/week, aligned to client's team time zone
Role Overview
Join a product-focused team to build and run the data pipelines behind customer-facing applications and analytics. You'll own your pipelines from first design through production support, with a focus on Microsoft Fabric.
Key Responsibilities
- Develop robust batch and streaming pipelines that pull data from APIs, databases, event streams, and external vendor systems.
- Create reusable patterns for ingesting, transforming, and storing data, and model it into consistent, trusted datasets.
- Build and troubleshoot workflows in Microsoft Fabric Notebooks and move them into production.
- Put automated testing, version control, and CI/CD around every pipeline you ship.
- Set up data quality checks, alerting, and monitoring so issues surface before users notice them.
- Tune queries, pipelines, and storage to keep runtime and cloud spend under control.
- Maintain clear documentation of data flows, lineage, and metadata.
- Work within agile ceremonies (planning, standups, retros) alongside product managers, developers, and analysts.
- Follow data privacy and security standards, and help mentor junior engineers.
Mandatory Skills
- Programming: Python, Java, or Scala for pipeline development
- Data Frameworks: Hands-on with at least two of Spark, Kafka, Flink, dbt
- Databases: Strong SQL plus working knowledge of No
SQL; solid data modeling fundamentals - Platform: Microsoft Fabric Notebooks, used in real project work
- Containers & Orchestration: Docker and Kubernetes
- Monitoring: Experience with observability tooling;
Datadog strongly preferred - Performance: Proven SQL and pipeline optimization for speed and cost
- Good to have: Fabric Lakehouse, Warehouse, Data Pipelines, Dataflows Gen2, Semantic Models;
Azure or AWS data services; CI/CD tools (Git Hub Actions, Jenkins, Azure Dev Ops); use of generative or agentic AI tools to speed up engineering work
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