Data Engineer

Ranger Technical Resources; Town of Florida (NY); On-site; USD 130,000 - 185,000; Full time

Job summary

Ranger Technical Resources seeks a senior data engineer to design and build scalable data pipelines on Databricks, advancing the Lakehouse architecture and data products for analytics and AI initiatives.

You will collaborate with BI, product, and development teams to raise data quality, governance, and engineering standards across the platform. A hands-on, mentorship role, leading architectural efforts and offshore partnerships.

Qualifications

• BS in Computer Science, Information Technology, or equivalent experience/field
• 7+ years of experience building modern data engineering solutions within cloud-based environments
• Hands-on expertise with Databricks, Lakehouse architectures, or comparable modern data platforms
• Strong track record building scalable ETL/ELT pipelines and data ingestion frameworks
• Exposure to ERP, operational, API, or enterprise business data within manufacturing, distribution, supply chain, retail, or similar industries

Responsibilities

• Design and build scalable backend data pipelines within Databricks.
• Develop trusted data products that support reporting, analytics, AI, and business applications.
• Build and enhance the organization's Lakehouse and data warehouse architecture.
• Design data ingestion processes for ERP systems, APIs, databases, and operational platforms.
• Create clean, well-modeled datasets that improve reporting accuracy and business insights.
• Improve data quality, governance, and engineering standards across the platform.
• Collaborate with Business Intelligence, Product, Application Development, and Master Data Management teams.
• Partner with offshore engineering resources by defining technical work and reviewing deliverables.
• Reduce technical debt through scalable architecture and reusable engineering patterns.
• Optimize pipeline performance, reliability, and maintainability.
• Support forecasting and operational analytics initiatives by delivering high-quality backend data.
• Evaluate technical solutions and contribute to architecture discussions.
• Mentor engineers through technical guidance and best practices.
• Help establish a scalable foundation for future AI and machine learning initiatives.
• Take ownership of key components of the enterprise data platform while remaining deeply hands-on.

Skills

Databricks

Lakehouse Engineering

ETL

ELT

Python

SQL

PySpark

Spark

Data Modeling

Data Products

API Integration

Data Warehousing

Airflow

Data Governance

Technical Ownership

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks Platform

Lakehouse Architecture

PySpark

Spark

Airflow

Job description

Our partner is an innovative manufacturing organization investing in a modern data platform that will power enterprise analytics, operational applications, forecasting, and future AI initiatives. Rather than maintaining existing pipelines, you'll help shape the foundation that helps the business scale its data capabilities for years to come.

This opportunity is ideal for a senior, hands-on Data Engineer who enjoys building platforms as much as solving technical problems. You'll design scalable data pipelines, develop trusted data products, improve the Lakehouse architecture, and create clean, well-modeled datasets that become the backbone for BI, internal applications, and machine learning initiatives.

The environment is collaborative, evolving, and highly technical. You'll work alongside Business Intelligence, Application Development, Product, and Master Data Management teams while helping establish engineering standards, improve data quality, and influence the long-term direction of the platform.

Experience and Education:

• BS in Computer Science, Information Technology, or equivalent experience/field
• 7+ years of experience building modern data engineering solutions within cloud-based environments.
• Hands-on expertise with Databricks, Lakehouse architectures, or comparable modern data platforms.
• Strong track record building scalable ETL/ELT pipelines and data ingestion frameworks.
• Exposure to ERP, operational, API, or enterprise business data within manufacturing, distribution, supply chain, retail, or similar industries.
• Demonstrated success supporting enterprise reporting, analytics, or AI initiatives through well-designed backend data platforms.

Skills and Strengths:

• Databricks
• Lakehouse Engineering
• ETL
• ELT
• Python
• SQL
• PySpark
• Spark
• Data Modeling
• Data Products
• API Integration
• Data Warehousing
• Airflow
• Data Governance
• Technical Ownership

Primary Job Responsibilities:

• Design and build scalable backend data pipelines within Databricks.
• Develop trusted data products that support reporting, analytics, AI, and business applications.
• Build and enhance the organization's Lakehouse and data warehouse architecture.
• Design data ingestion processes for ERP systems, APIs, databases, and operational platforms.
• Create clean, well-modeled datasets that improve reporting accuracy and business insights.
• Improve data quality, governance, and engineering standards across the platform.
• Collaborate with Business Intelligence, Product, Application Development, and Master Data Management teams.
• Partner with offshore engineering resources by defining technical work and reviewing deliverables.
• Reduce technical debt through scalable architecture and reusable engineering patterns.
• Optimize pipeline performance, reliability, and maintainability.
• Support forecasting and operational analytics initiatives by delivering high-quality backend data.
• Evaluate technical solutions and contribute to architecture discussions.
• Mentor engineers through technical guidance and best practices.
• Help establish a scalable foundation for future AI and machine learning initiatives.
• Take ownership of key components of the enterprise data platform while remaining deeply hands-on.