Principal Data Engineer Aspira - 3.3 Austin, TX Job Details 1 day ago Qualifications Data integrity assurance Data model design Data quality checks Commercial use (data warehousing systems) Cloud analytics services Data Integration (Data management) Schema design SQL Data quality management Data Architecture Design (Architecture design skills) Cloud database architecture Managing engineering teams Mentoring Leading team collaboration initiatives Database migration or upgrading Data performance optimization Technical architecture Python Dimensional modeling Full Job Description
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.- This role requires 3 days per week in office at our location in Austin, TX off of Bee Caves Road and Mopac
- About Aspira 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. 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. Position Overview 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. 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. Key Responsibilities Design, develop, maintain, and optimize scalable data pipelines, ETL workflows, and cloud-based data architectures within AWS environments. Build and support data warehouse, relational, and NoSQL database solutions using technologies such as PostgreSQL, Oracle SQL, and Snowflake. Implement data integration, migration, and modernization efforts, including work involving relational database platforms. Collaborate with cross-functional teams to understand data requirements, develop scalable data models, and support business intelligence and analytics initiatives. Write efficient, maintainable, and high-quality Python code while troubleshooting and optimizing data systems, queries, and pipelines. Apply best practices related to data engineering, data quality, governance, security, and operational reliability across all solutions and workflows. Support ongoing improvements to data infrastructure and tooling by evaluating and utilizing modern technologies and engineering practices. Contribute technical expertise, documentation, code reviews, and knowledge sharing within the engineering organization while working effectively in a collaborative, fast-paced environment. Required Experience 5-7+ years of experience in data engineering, including large-scale data architecture and ETL migration. 5+ years of hands-on experience with cloud and big data technologies such as Databricks, AWS Glue, Kinesis, Redshift, and DynamoDB. Data tool experience with Snowflake is preferred or other cloud data warehouses Strong expertise in relational databases, including PostgreSQL and Oracle SQL Proven experience with dimensional data modeling, data integration, and data quality management. Advanced proficiency in Python Experience designing and optimizing cloud-based data platforms within AWS environments. Demonstrated success leading technical teams and mentoring engineers. Preferred Qualifications Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field. Experience implementing data governance, security, and compliance best practices. Strong communication skills with the ability to translate complex technical concepts into business value. Experience working with geospatial data formats and frameworks such as GeoJSON, GeoParquet, H3, or related spatial data frameworks Familiarity with modern orchestration and data tooling such as Dagster.
