About this role
Job Type
Full-time
Description
On April 28, 2021, Avelo took flight as America’s first new airline in nearly 15 years – ushering in a new era of affordable, convenient, and reliable air travel. Founded and led by airline industry veteran, Andrew Levy, along with a team of world-class airline executives, we endeavored to build a different and better kind of airline with one mission in mind: “To inspire travel” and we’ve done so with industry-leading reliability and a caring Soul of Service. If you are looking for the opportunity to join a new and exciting airline that offers the chance to make your mark on aviation history, keep reading!
Purpose: The Data Engineer contributes to the design, development, and operation of the data infrastructure that powers our analytics and AI capabilities. Microsoft Fabric is the centerpiece of this role: you will help build and maintain notebook-based data pipelines, collaborate with analysts and Power BI developers, and grow your skills on a modern cloud data platform. This is a role for someone who is curious, detail-oriented, and ready to develop into a full-stack data engineering practitioner.
Core Responsibilities
- Pipeline & Notebook Development
- Assist in building and maintaining data pipelines under the guidance of senior engineers
- Write and maintain PySpark, Python, and SQL code for data ingestion, transformation, and loading
- Support implementation of medallion data architecture patterns (e.g., Bronze - Silver - Gold) to deliver clean, reliable datasets to downstream consumers
- Learn and apply software engineering best practices including version control, code review, and automated testing
- Participate in troubleshooting pipeline issues and help identify root causes
- Document data workflows, tables, and processes following established team standards
2. Data Quality & Observability
- Perform routine data quality checks to ensure accuracy, completeness, and consistency of datasets
- Define and implement automated data quality checks embedded directly into pipeline logic
- Support monitoring of pipeline health including data freshness, error rates, and row counts
- Help maintain documentation of data flows, schema changes, and source-system agreements
3. Platform Support
- Assist in maintaining and monitoring the cloud data platform environment
- Configure and enforce workspace-level access controls, row-level security (RLS), data encryption, and compliance policies; partner with IT Security on audit and certification requirements
- Track Fabric product updates and evaluate new capabilities (e.g., Real-Time Intelligence, Direct Lake, Fabric APIs); advocate for adoption where there is clear business value.
- Document all platform configurations, data flows, and operational runbooks in Microsoft Purview; maintain an accurate organizational data catalog and lineage map.
4. Collaboration & Communication
- Partner with analysts and BI developers to understand data requirements and deliver consistent, well-structured, documented datasets
- Translate business questions into defined data tasks with guidance from senior team members
- Participate in code reviews and contribute to shared repositories
- Communicate progress, questions, and blockers clearly to teammates and stakeholders
5. AI-Augmented Development
- Use AI development tools (Claude, Microsoft Copilot) as coding and documentation aids; apply critical review to all AI-generated outputs before committing to production
- Maintain awareness of AI data privacy obligations; escalate concerns to senior team members when appropriate
Requirements
Education & Experience:
- Bachelor's or Master's degree in Engineering, Computer Science, Mathematics, Data Science, or a related field; or equivalent practical experience
- 1-3 years of hands-on experience in data engineering, analytics engineering, software development, or a closely related technical role
- Demonstrated experience writing SQL queries and Python scripts for data processing or analysis
- Familiarity with at least one cloud data platform (Fabric, Azure, AWS, or GCP) through coursework, projects, or professional work
- Experience with Git or another version control system
Skills & Attributes:
- Solid foundation in SQL; comfortable writing joins, aggregations, and transformations independently
- Working knowledge of Python for data processing or automation tasks
- Understanding of core data concepts: relational vs. warehouse databases, schemas, data types, and basic data modeling
- Strong written and verbal communication; able to ask precise questions and explain your reasoning to both technical and non-technical audiences
- Systematic approach to troubleshooting -- investigates root causes rather than symptoms, and documents findings for future reference
- Genuine curiosity about data infrastructure and eagerness to learn new tools and platform capabilities
- Comfortable operating in a fast-moving environment where tools, features, and priorities evolve
X Factors:
Strong candidates will stand out in one or more of the following areas:
- Hands-on experience with Microsoft Fabric (workspaces, lakehouses, warehouses, or notebooks)
- Familiarity with the Azure data stack: Azure Data Factory, Azure Synapse Analytics, or Azure Data Lake Storage
- Experience with PySpark or distributed data processing frameworks (Databricks, Spark)
- Exposure to medallion architecture or equivalent layered data design patterns (Bronze/Silver/Gold)
- Familiarity with Microsoft Purview for data cataloging, lineage, or governance
- Exposure to real-time or near-real-time ingestion patterns (Eventstream, Kafka, Event Hubs)
- Experience in a regulated or operationally critical industry (aviation, finance, healthcare) where data reliability directly impacts business outcomes
- Prior exposure to AI-augmented or agentic workflows in a data engineering context
May perform other responsibilities as assigned. Responsibilities and duties may change when circumstances dictate (e.g., emergencies, changes in workload, etc.).
Avelo is an equal opportunity employer.
Salary Description
$85,000-$95,000 annually
