Principal Data Engineer
Role details
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Tech stack
Job description
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., * 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.
Requirements
- 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.