Principal Data Engineer at Aspira

<p style="text-align: center;"><strong>***Please Note: Applicants must be legally authorized to work in the United States. Aspira is unable to sponsor or take over sponsorship of employment visas, now or in the future.***<br>**This role requires 3 days per week in office at our location in Austin, TX off of Bee Caves Road and Mopac**</strong></p> <h4>About Aspira</h4> <p>For forty years, Aspira has been the market-leading software and services provider for the great outdoors, primarily for state and provincial parks and wildlife agencies. As part of our constant evolution, we're executing an aggressive multi-year transformation to accelerate revenue growth, optimize cost structures, and maximize shareholder value while expanding our market position.</p> <p>The leadership team has reset the company's core values to drive our transformation: Customer Obsession, Forward Momentum, One Team One Dream, Radical Transparency, Win with Integrity, and Excellence guide everything we do.</p> <h4>Position Overview</h4> <p>As a Principal Data Engineer at Aspira, you will contribute to the development, optimization, and maintenance of scalable, cloud-based data platforms and architectures that support analytics, operational efficiency, and business growth. This role requires strong hands-on technical expertise in data engineering, ETL development, cloud technologies, and database design within modern enterprise data environments.</p> <p>You will work closely with data scientists, analysts, product managers, and engineering teams to deliver secure, scalable, and reliable data solutions. The ideal candidate is a senior-level individual contributor who thrives in a collaborative environment, executes effectively on assigned initiatives, and brings deep technical knowledge to complex data engineering challenges.</p> <h4><span style="text-decoration: underline;">Key Responsibilities</span></h4> <ul> <li>Design, develop, maintain, and optimize scalable data pipelines, ETL workflows, and cloud-based data architectures within AWS environments.</li> <li>Build and support data warehouse, relational, and NoSQL database solutions using technologies such as PostgreSQL, Oracle SQL, and Snowflake.</li> <li>Implement data integration, migration, and modernization efforts, including work involving relational database platforms.</li> <li>Collaborate with cross-functional teams to understand data requirements, develop scalable data models, and support business intelligence and analytics initiatives.</li> <li>Write efficient, maintainable, and high-quality Python code while troubleshooting and optimizing data systems, queries, and pipelines.</li> <li>Apply best practices related to data engineering, data quality, governance, security, and operational reliability across all solutions and workflows.</li> <li>Support ongoing improvements to data infrastructure and tooling by evaluating and utilizing modern technologies and engineering practices.</li> <li>Contribute technical expertise, documentation, code reviews, and knowledge sharing within the engineering organization while working effectively in a collaborative, fast-paced environment.</li> </ul> <h4><span style="text-decoration: underline;">Required Experience</span></h4> <ul> <li>5-7+ years of experience in data engineering, including large-scale data architecture and ETL migration.</li> <li>5+ years of hands-on experience with cloud and big data technologies such as Databricks, AWS Glue, Kinesis, Redshift, and DynamoDB.</li> <li>Data tool experience with Snowflake is preferred or other cloud data warehouses</li> <li>Strong expertise in relational databases, including PostgreSQL and Oracle SQL</li> <li>Proven experience with dimensional data modeling, data integration, and data quality management.</li> <li>Advanced proficiency in Python</li> <li>Experience designing and optimizing cloud-based data platforms within AWS environments.</li> <li>Demonstrated success leading technical teams and mentoring engineers.</li> </ul> <h4><span style="text-decoration: underline;">Preferred Qualifications</span></h4> <ul> <li>Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.</li> <li>Experience implementing data governance, security, and compliance best practices.</li> <li>Strong communication skills with the ability to translate complex technical concepts into business value.</li> <li>Experience working with geospatial data formats and frameworks such as GeoJSON, GeoParquet, H3, or related spatial data frameworks</li> <li>Familiarity with modern orchestration and data tooling such as Dagster.</li> </ul> <p>&nbsp;</p>