Data Engineer

Ranger Technical Resources; Town of Florida (NY); On-site; USD 110,000 - 160,000; Full time

Job summary

Ranger Technical Resources is looking for a Data Engineer to help modernize a slow, unstructured data environment. You will design and build data pipelines, enhance orchestration, and establish a foundation for faster, more reliable decision making across the business.

You will collaborate with business and technology leaders to translate requirements into scalable solutions, evaluate current data processes, and implement modern data platforms using Python, SQL, ETL/ELT, and cloud technologies.

Qualifications

• Background working in data engineering within evolving or unstructured environments.
• Ability to work directly with business stakeholders to gather requirements and translate operational needs into scalable technical solutions.
• Proven success designing and supporting data platforms that integrate information from multiple internal systems, external APIs, and third-party vendors.
• Prior work building or redesigning data pipelines from ingestion through delivery.
• Exposure to organizations modernizing legacy data processes and platforms.
• Familiarity with cloud-based data ecosystems and distribute data architectures.
• Experience evaluating technical tradeoffs and recommending scalable approaches based on business objectives.
• Experience in smaller or mid-sized organizations where adaptability, ownership, and problem-solving were critical to success.

Responsibilities

• Work closely with business and technology leaders to translate loosely defined requirements into scalable data solutions.
• Evaluate existing data processes and recommend improvements based on proven industry practices and business needs.
• Design and build modern data pipelines that ingest, transform, and deliver data across multiple systems.
• Integrate data from internal applications, external APIs, and third-party vendors into a unified and reliable platform.
• Replace manual and cron-based processes with scalable orchestration and workflow management solutions.
• Improve data quality, consistency, and reliability across a diverse set of data sources.
• Structure and model data to improve accessibility, usability, and long-term scalability.
• Contribute to the design and evolution of a modern data platform that supports real-time and near-real-time data access.
• Analyze system performance, identify bottlenecks, and optimize data processing to improve business visibility and decision-making.
• Collaborate with leadership on technical strategy, architecture decisions, and platform direction.
• Support reporting, analytics, operational insights, and future data science initiatives through well-structured and accessible data.
• Operate effectively in an evolving environment that requires ownership, adaptability, strong communication, and problem-solving skills.

Skills

Python

SQL

ETL

ELT

Workflow orchestration

Airflow

Data modeling

Data warehousing

Snowflake

Redshift

Data transformation

Business requirements analysis

Cloud computing

AWS

Product Mindset

Performance optimization

Problem solving

Education

Bachelor's degree in a relevant field

Master's degree in data engineering or related field

Tools

Airflow

Snowflake

Redshift

Job description

Our partner is a technology company building a scalable platform for cities and organizations to manage parking, payments, permits, and mobility operations. Their platform is driven by real-time data an d integrations across multiple systems. They are expanding their team with a Data Engineer to help modernize a slow, unstructured data environment. This person will focus on building pipelines, improving orchestration, and creating a stronger data foundation to support faster, more reliable decision making.

This is an opportunity to step into a data environment that is still taking shape and help define how it should work. You would focus on building the foundation of a modern data platform, designing how data moves, how it is structured, and how it becomes usable across the business. The work includes creating scalable pipelines, replacing manual processes, and improving access to data that supports real-world operations. It requires someone who can assess what exists, identify gaps, and move forward with practical solutions.

Experience and Education:

• Background working in data engineering within evolving or unstructured environments
• Ability to work directly with business stakeholders to gather requirements and translate operational needs into scalable technical solutions
• Proven success designing and supporting data platforms that integrate information from multiple internal systems, external APIs, and third-party vendors
• Prior work building or redesigning data pipelines from ingestion through delivery
• Exposure to organizations modernizing legacy data processes and platforms
• Familiarity with cloud-based data ecosystems and distributed data architectures
• Experience evaluating technical tradeoffs and recommending scalable approaches based on business objectives
• Experience in smaller or mid-sized organizations where adaptability, ownership, and problem-solving were critical to success

Skills and Strengths:

• Python
• SQL
• ETL
• ELT
• Workflow orchestration
• Airflow
• Data modeling
• Data warehousing
• Snowflake
• Redshift
• Data transformation
• Business requirements analysis
• Cloud computing
• AWS
• Product Mindset
• Performance optimization
• Problem solving

Primary Job Responsibilities:

• Work closely with business and technology leaders to translate loosely defined requirements into scalable data solutions
• Evaluate existing data processes and recommend improvements based on proven industry practices and business needs
• Design and build modern data pipelines that ingest, transform, and deliver data across multiple systems
• Integrate data from internal applications, external APIs, and third-party vendors into a unified and reliable platform
• Replace manual and cron-based processes with scalable orchestration and workflow management solutions
• Improve data quality, consistency, and reliability across a diverse set of data sources
• Structure and model data to improve accessibility, usability, and long-term scalability
• Contribute to the design and evolution of a modern data platform that supports real-time and near-real-time data access
• Analyze system performance, identify bottlenecks, and optimize data processing to improve business visibility and decision-making
• Collaborate with leadership on technical strategy, architecture decisions, and platform direction
• Support reporting, analytics, operational insights, and future data science initiatives through well-structured and accessible data
• Operate effectively in an evolving environment that requires ownership, adaptability, strong communication, and problem-solving skills