Data Engineer II

ABOUT BESTOW

Bestow is a leading insurance technology platform serving some of the world's largest and most innovative life insurers. We are on a mission to increase financial stability for everyone. Bestow is a team of mission-driven, results-oriented individuals. We offer all employees a remote (contiguous 48 only)/hybrid workplace, meaningful benefits, substantial growth opportunities, and equity.

Bestow participates in the E-Verify Program.

ABOUT THE TEAM

The Bestow Data Engineering team plays a significant role within the organization, working across the entire company to provide scalable data solutions within the platform and toward integrations with external partners. The data engineering team works closely with internal analytics team members in order to improve data architecture and serve data science predictions. In addition, data engineers work closely with stakeholders and members of product and engineering to design and launch new systems for extracting, transforming, and storing data. You’ll be called upon to improve Bestow’s data reliability, efficiency, and quality and will be expected to scale your solutions to the cloud environment of a SaaS company, iterate quickly, and make pragmatic choices around what tools and technologies to adopt.

ABOUT THE ROLE

• Build robust solutions for transferring data from first and third-party applications to and from our data warehouse
• Passionate about data quality and availability, driving to resolution through high collaboration with team members.
• Making decisions as a team. The things you build will be maintained and improved upon by others; there is a shared responsibility to make defensible design considerations.
• Develop hardened and repeatable (CI/CD) data models and pipelines to enable reporting, modeling, and machine learning.
• Improve data availability to our enterprise clients through a mix of traditional push delivery, cloud, and event-driven (eg: API, grpc) data sharing methods.
• Ensure data quality through automated monitoring and alerting, and occasionally serving within an on-call rotation.
• Leverage Google Cloud (GCP) tools (eg: Cloud Run, Cloud Function, Vertex AI, App Engine, Cloud Storage, IAM, etc.) and services (eg: Astronomer - Apache Airflow) to bring data workloads to production.
• Collaborate with product, engineering, stakeholders and data teams to deliver informed solutions to platform and client needs.

THIS ROLE REPORTS TO

• VP, Data Analytics
• Open to Dallas, TX, or Remote (US) #LI-Remote

YOUR EXPERIENCE

• 4+ years working in a data engineering role that supports incoming/outgoing feeds as well as analytics and data science teams
• 2+ years of Python or similar experience writing efficient, testable, and readable code
• Deep SQL experience with columnar databases such as Google BigQuery, Snowflake, or Amazon Redshift
• Comfortable designing an end-to-end data pipeline in cloud frameworks (such as GCP, AWS, Azure) with requirements from multiple stakeholders
• Experience building CICD pipelines for data processing using tools such as Docker, CircleCI, dbt, git, etc
• Able to manage infrastructure using IAC tools such as Terraform or Pulumi
• Experience with common data orchestration tools such as Apache Airflow (or similar) to manage SLOs and processing dependencies
• Experience in building streaming / real-time ingestion pipelines
• Experience with creating alerts and monitoring pipelines which contribute to overall data governance.
• Experience with containerization and container orchestration technologies with cloud architecture and implementation features (single- and multi-tenancy, orchestration, elastic scalability)
• Familiarity with standard IT security practices such as identity and access management (IAM), data protection, encryption, certificate, and key management.
• Adaptability to learn new technologies and products as the job demands.
• **Nice to have:* *experience with data contracts, data lakes, and API development.