Data Engineer I

About the Role

The Data Engineer I works with cross-functional teams to develop and support data ingestion, transformation, and reporting solutions for ZincFive's NiZn-based products, battery systems, manufacturing operations, and supporting technologies. This role contributes to the development and operation of data pipelines within ZincFive's Azure Databricks environment, helping make product, test, manufacturing, and operational data available for analysis. The Data Engineer I follows established architecture, development, testing, security, and data-governance practices and takes responsibility for delivering reliable, documented work within assigned areas. This role will work onsite at ZincFive headquarters in Tualatin, Oregon and reports to the Lead Software Engineer.

Key Responsibilities

• Develop and maintain data ingestion and transformation pipelines using Azure Databricks
• Implement assigned pipeline components using Python, SQL, Apache Spark, and Delta Lake
• Ingest data from files, cloud storage, databases, APIs, telemetry systems, and other approved sources
• Develop bronze, silver, and gold data transformations using established medallion architecture patterns
• Create and maintain Databricks notebooks, workflows, jobs, and supporting configuration
• Write automated tests and data-quality checks to verify pipeline correctness
• Monitor scheduled data jobs and assist with investigating pipeline failures and data-quality issues
• Perform data validation, reconciliation, troubleshooting, and defect resolution
• Assist with schema development, table design, data mapping, and source-to-target documentation
• Support the onboarding of new datasets into Unity Catalog
• Follow established security, access-control, naming, lineage, and data-governance practices
• Participate in code reviews, design reviews, sprint planning, and technical discussions
• Maintain technical documentation for pipelines, tables, data sources, and operational procedures
• Communicate progress, risks, and technical issues to engineering leadership and project stakeholders
• Work with cross-functional teams to understand data requirements and deliver defined data solutions
• Support continuous improvement of pipeline reliability, performance, maintainability, and cost efficiency
• Ability to work independently and as part of a team
• Other duties as assigned

Requirements & Tech Stack

• Bachelor's degree in computer science, data science, software engineering, information systems, engineering, or a related field
• 0-2 years of professional experience in data engineering, software development, analytics engineering, or a related field
• Experience using Python and SQL through coursework, internships, personal projects, or professional work
• Familiarity with relational data, schemas, joins, aggregations, and data-transformation concepts
• Familiarity with data pipelines, ETL processes, and structured data formats
• Basic understanding of software-development practices, including version control and code review
• Ability to troubleshoot technical problems and learn unfamiliar systems
• Ability to follow established technical designs and engineering standards
• Technical documentation skills
• Demonstrates effective communication, organization, collaboration, and problem-solving skills

Preferred Experience/Skills

• Experience with Azure Databricks, Apache Spark, or PySpark
• Familiarity with Delta Lake and medallion data architecture
• Familiarity with Microsoft Azure services, particularly Azure Data Lake Storage
• Familiarity with Databricks Workflows, Unity Catalog, or Databricks Asset Bundles
• Experience working with REST APIs, JSON, CSV, Parquet, or time-series data
• Experience creating automated tests or data-quality checks
• Familiarity with Git, GitHub, CI/CD, and infrastructure or configuration as code
• Familiarity with dashboards, business intelligence tools, or data visualization
• Internship, academic, or project experience building an end-to-end data pipeline
• Experience with industrial telemetry, manufacturing data, battery systems, laboratory test data, or Internet of Things data

Key Competencies

• Attention to detail and organizational skills
• Excellent communication skills – verbal and written
• Good judgment with solid decision making
• Customer service orientation
• Teamwork and collaboration
• Continuous improvement

Physical Requirements and Working Conditions

• Work involves sitting, repetitive motion, occasional walking, and lifting up to 15 pounds
• Normal office/lab environment
• Ability to wear appropriate PPE when required