Data Engineer

Data Engineer

We're seeking a hands-on Data Engineer to join our cross-functional platform team, partnering with Data Scientists, Analysts, Engineers, and Architects to build scalable data streaming, analytics, and machine-learning solutions in the Azure Databricks ecosystem. If you thrive on solving complex data challenges and delivering high-impact data products, this is the role for you.

What You'll Do :

Design & Build Pipelines : Develop, test, and maintain end-to-end data pipelines (batch and streaming) using Azure Databricks, Kafka, Spark, and Neo4j.

Streaming Data : Architect and support real-time data pipelines, ensuring low-latency, high-throughput delivery in Kafka and Databricks environments.

Data Quality & Validation : Implement robust validation and monitoring to detect, diagnose, and resolve data issues quickly.

Collaboration : Work closely with Data Science to productionize ML models, and with BI teams to curate and deliver reliable datasets for reporting and dashboards.

Technical Communication : Translate complex technical requirements into clear designs and articulate solutions to both technical and non-technical stakeholders.

What You Bring :

Proven Experience : 3+ years building and maintaining Python / Java / Scala applications in a distributed data environment.

Big Data Expertise : 2+ years with Data Lake architectures, Spark / Databricks development or administration, and Kafka streaming.

Cloud Proficiency : Hands-on experience with Azure servicesDatabricks, Azure Services, and related infrastructure.

Analytical Mindset : Strong problem-solving skills in distributed computing, with the ability to optimize performance and scalability.

Machine Learning in Production : Experience deploying and monitoring Data Science / ML models as part of data products.

Software Engineering Best Practices : Solid coding skills (Java, Python, Spark, SQL), with experience in testing, code reviews, CI / CD, and version control.

Data Visualization : Comfortable analyzing data and building dashboards (e.g., Power BI, Python visualization libraries).

Quick Learner : Able to rapidly understand new business domains and transform requirements into technical deliverables.

Education :

Bachelor's, Master's, or PhD in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

U-Haul is an equal opportunity employer. All applications for employment will be considered without regard to race, color, religion, sex, national origin, physical or mental disability, veteran status, or any other basis protected by applicable federal, provincial, state, or local law. Individual accommodations are available on requests for applicants taking part in all aspects of the selection process. Information obtained during this process will only be shared on a need to know basis.