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Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
The Senior Data Engineer develops and maintains data pipelines, evaluates business requirements, integrates data, ensures quality, and collaborates with teams to fulfill data infrastructure needs.
Top Skills:
AWSAzureBig Data ProcessingEtl FrameworksGCPKafkaKubernetesNoSQLPythonScalaSparkSQL
Cannabis • eCommerce • Enterprise Web • Logistics • Payments • Software • Database
Lead the evolution of data platform by designing scalable pipelines, improving data processes, mentoring teams, and modernizing data architecture.
Top Skills:
AirflowAWSDbtFivetranLambdaPythonRedshiftSigma
Insurance
The Senior Data Engineer will architect, build, and maintain scalable data pipelines and infrastructure, mentor junior engineers, and collaborate on data solutions for Openly's insurance platform.
Top Skills:
AivenSparkBigQueryDebeziumGCPGoKafkaPostgresPythonSQLTerraform
At Goldbelly, we believe food brings people together. We connect people with their greatest culinary desires within and beyond local communities. We empower food makers of all sizes and deliver their passion to food-lovers around the country.
As a Data Engineer, you will enhance how millions of customers connect with both novel and nostalgic food experiences on our platform. By partnering with business leaders and leveraging state-of-the-art data engineering and analytics resources, you will play a key role in transforming our data infrastructure and pipelines.
Responsibilities- Collaborate closely with full stack engineers, machine learning engineers, data analysts, and product managers to design and optimize data pipelines and ETL processes that drive business decisions.
- Design, develop, and maintain robust, scalable data systems to ensure seamless data integration and high availability.
- Improve our data infrastructure by optimizing ingestion, storage, and retrieval processes to support analytics, reporting, and machine learning applications.
- Help define and ensure data quality, governance, and security best practices are followed across all data workflows.
- Build and maintain data models that support business insights and operational reporting.
- Apply software engineering best practices, including CI/CD, testing, and version control, to data engineering workflows to ensure reliability and maintainability.
- 3+ years of experience in data engineering and working on large-scale data systems.
- Expert level in SQL required, proficiency in Python preferred.
- Skilled in dimensional and normalized data modeling and transformation using tools like dbt Cloud.
- Strong understanding of cloud-based data infrastructure (AWS and Snowflake preferred).
- Experience with BI platforms like Metabase and Sigma Computing for data visualization/dashboard tools.
- Experience with data ingestion and ETL pipelines like Fivetran.
- Familiarity with event-driven architectures and real-time data streaming using tools like Confluent Kafka.
- Proficient in version control with Git and collaborative development on GitHub or GitLab.
Salary range: $140,000 - $190,000 base salary range (dependent on experience level and interview performance) + equity (incentive stock options, vested over 4 years) + benefits.
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center



