Data Engineer

Vagaro•Pleasanton, CA

2d•$135,000 - $150,000•Onsite

About The Position

Vagaro is seeking a skilled Data Engineer to join our dynamic team and partner with our Data Science, Machine Learning, and Business Intelligence teams to build enterprise-grade data solutions. As a Data Engineer at Vagaro, you will play a critical role in designing and maintaining scalable data architectures on the Microsoft Fabric platform. You will lead the design and optimization of ETL/ELT pipelines, establish data governance standards, and ensure seamless data integration across multiple platforms and data sources. Your expertise will directly enable our teams to deliver reliable, high-performance data infrastructure that supports real-time analytics, machine learning model training, and business intelligence initiatives. This role is based onsite in Pleasanton, CA Monday through Friday

Requirements

Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related technical field.
3-5 years of experience as a Data Engineer or similar role.
Experience designing and maintaining enterprise-scale ETL/ELT solutions.
Hands-on experience with Microsoft Fabric, including data migration projects.
Strong experience with relational and NoSQL databases.
Experience building modern cloud-based data platforms in Azure (AWS or GCP experience is also beneficial).
Experience with DevOps practices, CI/CD pipelines, and Infrastructure as Code.
Expert-level SQL.
Strong Python development skills.
Experience with PySpark
Experience with Pandas
Experience with Spark
Strong understanding of data modeling, dimensional modeling, and schema design.
Experience working with SQL Server
Experience working with NoSQL (MongoDB, Elasticsearch, etc.)
Experience working with Azure Data Lake Storage
Experience working with Delta Lake
Experience working with Parquet
Familiarity with REST APIs and data integration patterns.
Experience working with large-scale structured and semi-structured datasets.
Excellent analytical and problem-solving abilities.
Strong communication and collaboration skills.
Ability to work independently while collaborating across multiple teams.
Strong attention to detail and commitment to data quality.

Nice To Haves

Experience with Azure DevOps or GitHub Actions.
Experience with Docker and Kubernetes.
Experience implementing monitoring, observability, and alerting for enterprise data platforms.

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines to ingest, transform, and store data from a variety of internal and external data sources.
Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
Monitor, troubleshoot, and resolve data pipeline failures and performance issues.
Develop reusable Python libraries and frameworks to standardize data engineering solutions.
Build and maintain CI/CD pipelines to automate deployment, testing, and release processes.
Experience integrating with REST APIs to ingest, transform, and process data from external systems.
Design, implement, and maintain enterprise data solutions using the Microsoft Fabric platform.
Build and optimize Fabric Warehouses, Lakehouses, Semantic Models, and Data Pipelines.
Define enterprise Fabric architecture, workspace strategy, security model, and governance standards.
Manage Fabric capacities, optimize compute utilization, and monitor platform health and performance.
Lead capacity planning, workload isolation, reservation management, and cost optimization across Business Intelligence, Data Engineering, and Machine Learning workloads.
Implement monitoring, alerting, logging, and operational best practices for Fabric environments.
Design and maintain scalable data models and enterprise data architectures.
Implement data governance, security, lineage, and metadata management best practices.
Ensure data quality, integrity, availability, and compliance across all data platforms.
Maintain comprehensive documentation for data pipelines, architectures, standards, and operational procedures.
Partner with Data Scientists and Machine Learning engineers to provide reliable data infrastructure for model training and deployment.
Collaborate with Business Intelligence teams to ensure timely and reliable data availability for reporting, dashboards, and analytics.
Work closely with business stakeholders, analysts, and software engineers to understand requirements and deliver scalable data solutions.
Evaluate emerging technologies and recommend improvements to the data platform.
Continuously improve data engineering processes, automation, and operational efficiency.
Participate in architecture reviews, code reviews, and mentoring to promote engineering best practices.

Benefits

Competitive salary
Performance-based bonuses
15 accrued days of PTO
10 company holidays annually
Comprehensive healthcare, dental, and vision plans
Discounts on attractions, theme parks, shows, sports events, movies, hotels, and more through TicketsAtWork
$30/month reimbursement for any Vagaro service, including health, beauty, or wellness treatments
$50 monthly stipend for onsite microkitchen
Complimentary DoorDash DashPass subscription
College Assistance Reimbursement
Access to EAP & Work/Life Programs
LinkedIn Learning account
401k program with 4% matching
Optional life/supplemental insurance
Access to on-site gym
Flavored water dispenser
Basketball court