[Hiring] Senior Data Engineer @Openly

Role Description

We are seeking a Senior Data Engineer to be a technical leader on our data engineering team. This role involves designing and delivering robust, scalable data solutions for Openly's insurance platform. You will apply deep expertise across the data lifecycle—from architecture and pipeline design to optimization and mentoring—to shape how we build, manage, and access data for our products and business intelligence.

Key Responsibilities

• Architect, build, and maintain high-quality, scalable data pipelines, data models, and data infrastructure across our GCP-based platform.
• Lead technical design decisions related to data architecture, pipeline orchestration, data modeling, and cloud infrastructure.
• Develop and optimize complex SQL queries and data transformations in BigQuery and PostgreSQL, ensuring performance, reliability, and correctness.
• Write production-grade code in Python and/or Go to build and enhance data management frameworks, services, and pipeline tooling.
• Partner with data science, business intelligence, product, and operations teams to translate business requirements into reliable data solutions.
• Own and improve the full Software Development Lifecycle (SDLC) for data projects: design, development, testing, CI/CD deployment, monitoring, and maintenance.
• Leverage streaming and event-driven architectures using Kafka (Aiven/Debezium) to build real-time data pipelines.
• Utilize and optimize distributed data processing frameworks such as Apache Spark for large-scale data transformations.
• Mentor and provide technical guidance to junior and mid-level data engineers; conduct code reviews and promote engineering best practices.
• Share your knowledge within the data engineer team and the engineering organization through all-hands presentations, learning hours, domain meetings, and written documentation.

Our Stack

• Backend/Core: Go & Postgresql
• Frontend: Browser-based, VueJS, Vite, Webpack, Nuxt & Tailwind
• Research/Data Science: R, ArcGIS, Vertex, & Python
• Data: GCP GCS, BigQuery, Composer/Airflow, Cloud Functions, Postgres, SQL, Python, Aiven Debezium and Kafka, Fivetran
• Infrastructure: Google Cloud, specifically Cloud Run, Kubernetes, Pub/Sub, BigQuery, and CloudSQL, managed with Terraform.
• Remote work tools: Slack, Zoom

Qualifications

• 4+ years of data engineering and data management experience, with a proven track record of delivering complex, production-grade data systems.
• Strong proficiency in SQL and SQL optimization — including query tuning, indexing strategies, execution plan analysis, and data modeling in BigQuery and PostgreSQL.
• Expert-level scripting and programming in Python; experience with Go is a strong plus.
• Deep expertise with Google Cloud Platform (GCP), including BigQuery, GCS, Composer/Airflow, Cloud Functions, Cloud Run, Pub/Sub, and CloudSQL.
• Proven experience building and operating event-driven and streaming data pipelines using Kafka or similar technologies (Aiven/Debezium experience a plus).
• Strong understanding of modern data warehouse and Lakehouse architectures, including multi-layered data modeling patterns (bronze/silver/gold or equivalent).
• Infrastructure as Code (IaC) experience with Terraform to define, manage, and version cloud data infrastructure.
• Solid understanding of Software Development Lifecycle (SDLC) best practices: CI/CD pipelines, automated testing, code review processes, code repositories, and deployment management.
• Experience with data replication tools (e.g., Fivetran, Debezium) and understanding of CDC (Change Data Capture) patterns.
• Ability to independently drive data architecture decisions, translate business requirements into source-to-target data mappings, and deliver working, maintainable solutions.
• Strong communication skills; able to effectively collaborate with and educate both technical and non-technical stakeholders.
• Experience mentoring engineers and leading technical initiatives within a team environment.

Nice to Have

• Hands-on experience with Apache Spark or other distributed data processing frameworks for large-scale batch and/or streaming workloads.
• Familiarity with data observability and monitoring tools (e.g., DataDog, Monte Carlo, Great Expectations).
• Prior experience in a regulated industry such as insurance, finance, or healthcare.
• Contributions to open-source data engineering projects or internal data platform tooling.
• Experience with AI tools such as Claude, Copilot or equivalent.

Compensation & Benefits

• Budgeted Salary Range: $140,800 — $158,400 USD
• Full Salary Range: $140,800 — $211,200 USD
• Remote-First Culture - We supported #remotelife long before it was a given. We'll keep promoting it.
• Competitive Salary & Equity
• Comprehensive Medical, Dental, and Vision Plan Offerings
• Life and disability coverage including voluntary options
• Parental Leave - up to 8 weeks (320 hours) of paid parental leave based on meeting eligibility requirements
• 401K Company Contribution - Openly contributes 3% of the employee's gross income, even if the employee does not contribute.
• Work-from-home stipend - We provide a $1,500 allowance to spend on setting up your home workplace.
• Annual Professional Development Fund: Each employee has $2,000 in professional development (PD) funds to spend on activities or resources annually.
• Be Well Program - Employees receive $50 per month to use towards your overall well-being.
• Paid Volunteer Service Hours
• Referral Program and Reward