Engineering Manager, Data Engineering (Remote, US)

Openly is rebuilding insurance from the ground up. We are re-envisioning and enhancing every aspect of the customer experience. Doing this requires a rapidly growing team of exceptional, curious, empathetic people with a wide range of skill sets, spanning technology, data science, product, marketing, sales, service, claims handling, finance, etc.

We created Openly because we saw an evident gap in the market for premium insurance made simple. Consumers deserve more complete coverage at competitive prices.

• The Price Difference: Using cutting-edge data and technology, we provide you with customizable, competitive prices to protect your most valuable assets.
• The Policy Difference: Coverages are truly customizable to meet your individual protection needs, for both standard coverages and optional add-ons.
• The Experience Difference: From tailored claims handling to highly responsive customer service, we are focused on making the home insurance purchasing process a better overall experience.

At Openly, our people are just as important as our product. For us, collaboration, communication, and work-life balance are more than nice-to-haves— they’re the must-haves that make us who we are. We believe a great company is the result of a shared set of values, so we look for these qualities in every candidate we hire. 

• Integrity
• Empathy
• Teamwork
• Curiosity
• Urgency

We've designed our hiring process with you, the candidate, in mind. At every step, you have the chance to present your strengths and learn more about what makes Openly a great place to work.

We embrace individuality and believe diverse teams are winning teams. Our commitment to inclusion across race, gender, age, religion, identity, and experience drives us forward every day.

We’re hiring a Engineering Manager, Data Engineering to drive our Data Engineering team’s people, projects, and processes forward. At Openly, our growth has put an emphasis on building and maintaining a robust, scalable data platform to ensure teams can access high-quality data efficiently. Our data engineering function is responsible for designing and maintaining data pipelines, data architectures, and data infrastructure while working closely with data science, business intelligence, and product teams to enable data-driven decision-making across the organization.

As the Engineering Manager of the Data Engineering Team, you will provide technical leadership and influence decisions about data architecture, data pipeline strategies, and technical processes. You will drive our data engineering culture, manage and mentor a diverse group of data engineers, and work strategically across teams to ensure our data platform evolves with business needs. While this is primarily a leadership role, this position will also have the capacity to pick up technical work during periods of high demand, demonstrating technical credibility with the team and staying connected to the evolution of our data systems.

• →Manage, support, and mentor a diverse group of data engineers
• →Partner with the Principal Engineers and engineering leadership to guide the data architecture, scalability, and evolution of our data platform
• →Work closely with data science, business intelligence, and product teams to align data solutions with business objectives, balancing technical investments with business priorities
• →Identify, resolve, or escalate roadblocks and risks that threaten team deliverables and goals, seeking additional context or direction when needed
• →Drive each team member toward their career goals through clear milestones, transparent feedback, and a culture of open communication that sets them up for success
• →Translating data concepts and requirements into architecture decisions and technical implementation strategies
• →Provide technical input on data pipeline design, data modeling, and technology selections
• →Contribute hands-on technical work during peak periods to support the team and maintain technical credibility
• →Establish best practices for data pipeline architecture, data quality, and performance optimization
• →Runs cross functional working groups to deliver on larger company objectives
• →Participate in domain standups, weekly 1:1s, team collaborations, biweekly demos, and biweekly retros
• →Share your knowledge within the data engineering team and with others in the company (e.g., engineering all-hands, engineering learning hour, domain meetings)
• →Partner closely with the management team, HR, and Recruiting to attract, recruit, and develop a diverse team of high-quality data engineers

• Backend/Core: Go & PostgreSQL
• Frontend: Browser-based, VueJS, Webpack, Nuxt & Tailwind
• Research/Data Science: R, VertexAI, Hex, & Python
• Data: GCP GCS, BigQuery, Composer/Airflow, Cloud Functions, PostgreSQL, SQL, Python, Aiven Debezium and Kafka, Fivetran
• Infrastructure: Google Cloud (Cloud Run, Kubernetes, Pub/Sub, BigQuery, CloudSQL), managed with Terraform. GitHub for code hosting, DataDog for monitoring, CircleCI for CI/CD pipelines Remote work tools: Slack, Zoom

If you don’t think you meet all of the criteria below but still are interested in the job, please apply. Nobody checks every box, and we’re looking for someone excited to join the team.

• 5+ years of data engineering and data platform development experience, including 3+ years of engineering management or technical leadership in a data/infrastructure/operations environment
• Deep experience with data infrastructure components, including data lakes and lakehouses (e.g., Iceberg), data warehouses (e.g., Snowflake, BigQuery), online and offline data stores, and both batch and real-time streaming systems
• Proven, hands-on expertise designing and maintaining scalable, secure, and cost-efficient data platforms and pipeline architectures — including schema design, data modeling, partitioning, data replication, staging, transformation, and movement — aligned to business goals and objectives
• Comfortable working with modern data and infrastructure technologies, such as Spark, Flink, Kafka, Airflow, Kubernetes, and similar tools
• Experience with Google Cloud data technologies (BigQuery, Cloud Composer, GCS, etc.) or similar cloud data platforms
• Infrastructure as Code (IaC) experience with Terraform to define, manage, and version cloud data infrastructure
• Proficiency in Python or similar languages (e.g., Java, Scala), with strong SQL skills and performance tuning for analytical workloads
• Understanding of data governance, security, and compliance best practices (e.g., RBAC, PII handling, auditability), with experience designing systems that meet regulatory and internal standards
• Demonstrated ability to understand data requirements, translate them into source-to-target data mappings, and build scalable solutions
• Experience guiding and mentoring a diverse group of engineers while balancing their growth with business requirements
• Highly autonomous with the ability to prioritize and work through ambiguity
• Ability to effectively communicate technical and strategic concepts to diverse audiences
• Experience or familiarity with agile methodologies and strong organizational skills