Data Engineer I

ZincFive, Inc. is hiring a Data Engineer I to develop and support data pipelines and reporting solutions for its products, battery systems, manufacturing operations, and supporting technologies. The role contributes to making product, test, manufacturing, and operational data available for analysis using Azure Databricks and established engineering and governance practices.

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

Preferred

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

Azure Databricks

Apache Spark

PySpark

Delta Lake

Medallion Data Architecture

Microsoft Azure

Azure Data Lake Storage

Databricks Workflows

Unity Catalog

Databricks Asset Bundles

REST APIs

JSON

CSV

Parquet

Time-Series Data

Automated Testing

Data Quality Checks

Git

GitHub

CI/CD

Infrastructure as Code

Configuration as Code

Dashboards

Business Intelligence Tools

Data Visualization

End-to-End Data Pipelines

Industrial Telemetry

Manufacturing Data

Battery Systems

Laboratory Test Data

Internet of Things Data

Benefits

Medical insurance

Dental insurance

Vision insurance

Life insurance

401k

Paid sick time

Paid time off for vacation

Paid holidays

Paid community service days

Professional/personal learning program

Applicable state/federal paid family leave

Company

Nickel-zinc batteries and immediate power solutions

Tualatin, Oregon, USA

http://www.zincfive.com/

Founded in 2016

51-200 employees

Qualifications

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

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

Required skills

Python, SQL, Relational Data, Data Pipelines, ETL, Version Control, Azure Databricks, Apache Spark, Delta Lake, Medallion Architecture, Microsoft Azure, Azure Data Lake Storage, Unity Catalog

Preferred skills

Experience with Azure Databricks, Apache Spark, or PySpark, Familiarity with Delta Lake and medallion data architecture, Experience creating automated tests or data-quality checks

Experience

Entry level