Engineer- Data Platform

Natural Habitat Adventures•Louisville, CO

1d•$75,000 - $90,000•Hybrid

About The Position

Natural Habitat Adventures is seeking a Level 2 Engineer, Data Platform to join its Technology & Information Systems team. The role builds, owns, and improves data platforms and integrations that support the business, primarily using Snowflake, SQL, dbt, Python, and cloud-based data services. The engineer ingests, models, transforms, tests, and maintains business data; designs dimensional models; owns pipeline quality and performance; and works with business stakeholders to develop reliable data products. The position works independently on standard tasks, owns work from requirements through release, and helps onboard newer engineers. This is a full-time, exempt hybrid position based in the company's Louisville, Colorado office, with at least three days per week on-site. Employees also attend an annual company-wide in-person staff week and an additional department-scheduled in-office week each year. Standard company hours are Monday through Friday, 8:00 AM to 5:00 PM MT; additional hours may be required as needed. The role offers a starting salary of $75,000–$90,000 per year and eligibility for a discretionary annual bonus with a target incentive equal to 5% of salary.

Requirements

Strong SQL skills, including complex joins, window functions, and performance tuning.
Proficiency in Python, including scripting and libraries such as pandas.
Solid understanding of relational (OLTP) and dimensional (OLAP / Kimball) data modeling.
Hands-on experience with Snowflake or a similar cloud data platform, and dbt or a similar tool.
Experience building ETL/ELT pipelines, including ingestion, transformation, testing, and monitoring.
Experience with REST APIs and JSON.
Proficiency with Git, pull requests, CI/CD, and release management.
Knowledge of fundamental software development concepts, including functions, variables, data structures, error handling, and testing.
Experience supporting data systems in production.
Bachelor's degree in Computer Science, Software Engineering, Data Science, Information Systems, Information Analytics, Statistics, or a related field, or equivalent practical experience.
2–4 years of experience in data engineering, analytics engineering, or software development.
Track record of delivering projects with minimal oversight, ideally on a Scrum or agile team.
Ability to turn vague requests into clear requirements and plans.
Clear communication with technical and non-technical audiences.
Exceptional organizational and communication skills and ability to thrive in a collaborative, mission-driven environment.

Nice To Haves

Experience with cloud platforms such as AWS or Azure.
Experience with orchestration or scheduling tools.
Experience with data visualization or business intelligence (BI) tools.
Experience with data governance, access control, or data quality frameworks.
Experience with web application development.
Experience with infrastructure as code (IaC).

Responsibilities

Work with relational and dimensional data models for defined business processes, including facts, dimensions, grain, keys, and table relationships.
Build and maintain reliable pipelines and dbt models from source systems through the reporting layer.
Create shared, reusable data models and metrics for multiple use cases.
Develop and maintain Python scripts and data-processing workflows.
Load and transform data from operational systems, APIs, and other sources into the enterprise data platform.
Own pipeline data quality through testing, monitoring, alerting, and documentation.
Tune queries and pipelines for performance and cost.
Apply and help refine team standards for data modeling, naming, keys, relationships, and data quality.
Document data models, pipelines, processes, and technical decisions.
Develop working knowledge of data supporting bookings, guests, trips, operations, finance, and other core business processes.
Gather stakeholder requirements and translate them into data logic.
Develop small application features and internal tools under senior engineer guidance.
Build and maintain integrations between applications and data systems, including REST APIs and other services.
Break work into small, shippable pieces and estimate it.
Apply best practices for Git, code review, CI/CD, and release management.
Write unit and integration tests as part of regular work.
Understand and monitor code running in production, including monitoring and alerting.
Research and attempt solutions independently before seeking help; bring problems, options, and recommendations when a decision is needed.
Work independently across several projects and as part of a Scrum team.
Own features and data products from requirements through release and monitor their subsequent performance.
Raise blockers early enough to protect deadlines.
Drive escalated tickets to resolution and identify recurring issues to automate or improve.
Work with senior engineers, analysts, data architects, and business stakeholders.
Document technical decisions, runbooks, and design notes.
Explain technical constraints, tradeoffs, and findings in plain language, and keep stakeholders informed of progress, risks, and scope changes.
Help onboard new team members and Level 1 Engineers.
Provide thoughtful code reviews and share knowledge through pairing and demonstrations.
Suggest improvements to team standards and tools.