USASenior Analytics Engineer (AI Insurance SaaS)
1 мес. назад
USASenior
data modelingbusiness intelligencedata platformanalyticsai
Senior Analytics Engineer role focused on building and scaling AI-driven analytical data platform for insurance SaaS.
Требования
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 5+ years of experience in data engineering, with a focus on building analytical data platforms.
- Demonstrated experience with cloud data warehousing solutions (e.g. BigQuery, Snowflake, Redshift).
- Strong proficiency in SQL and experience with data modeling techniques (e.g., star schema, dimensional modeling).
- Experience building and maintaining ETL/ELT pipelines using tools like Dagster, Apache Airflow, dbt, or similar.
- Experience with programming languages such as Python, Java, or Scala.
- Experience with data governance and data quality tools and processes is highly desirable.
- Excellent problem-solving and analytical skills, along with passion for data and a commitment to data quality.
Условия
- Compensation: The base salary range is $200-225K, with flexibility depending on a candidate’s background and experience. An annual bonus plan and company equity plan (RSUs) are also included in our compensation package.
- Well-Being: Medical, dental, vision, short & long-term disability, life insurance and AD&D, and 401k matching. Additional family, wellness, and pet benefits.
- Home & Family: Paid time off and sick leave, 100% paid parental leave (16 weeks for primary caregivers and 12 weeks for secondary caregivers). We offer a flexible schedule for new parents returning to work.
- Office Life: Catered lunches, happy hours, pet-friendly spaces, and monthly technology stipend.
- Growth & Training: $1,000/year for each employee for professional development, as well opportunities for tuition reimbursement.
- Sponsorship: We are open to sponsoring candidates currently in the U.S. who need to transfer their active visa. Please check with our Recruiting team if your visa is applicable for transfer.
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- appreciates your interest in our company as a place of employment. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Другое
- About Us: ’s mission is to improve the lives of injured and disabled workers and enable them to return to the workforce, saving billions of dollars in avoidable costs and lost productivity to the US and global economies and make insurance more affordable for everyone. We are currently experiencing massive growth and to accomplish our goals, we are hiring world-class talent who want to help build and scale internally, and transform the insurance space. Our team is our #1 priority, and we have been named one of Inc.’s Best Workplaces 3 years in a row!
- The Adventure: We're the leading AI Guidance Platform in the insurance industry today, working with some of the largest insurance carriers in the US and expanding globally. We are seeking a highly skilled and motivated Senior Analytics Engineer to play a pivotal role in building and scaling our next-generation analytical data platform. This role will be instrumental in shaping our analytics strategy, designing robust data models, and ensuring the availability, accuracy, and performance of our business intelligence data assets. As a key member of our team, you will collaborate closely with data scientists, analysts, and other engineers to deliver data-driven insights that drive critical business decisions.
- Lead the design, development, and implementation of a scalable, reliable, and efficient analytical data platform.
- Influence decisions on technology and tool selection for data ingestion, storage, transformation, and analysis for the analytics platform.
- Contribute to the overall data architecture and strategy, ensuring alignment with business needs and best practices.
- Build and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources into the data warehouse (e.g., cloud storage, databases, APIs).
- Develop and optimize data models for analytical use cases, ensuring data quality, consistency, and accessibility.
- Establish and enforce data quality standards and processes to ensure data accuracy and integrity.
- Implement data governance policies and procedures to manage data access, security, and compliance for analytics use cases
- Proactively identify and address data quality issues, working with stakeholders to resolve root causes.
- Partner with data scientists, analysts, and other engineers to understand their data needs and provide solutions.
- Effectively communicate technical concepts and designs to both technical and non-technical audiences.
- Mentor and guide data engineers, fostering a culture of learning and collaboration.
- Stay up-to-date on the latest trends and technologies in data engineering and analytics.
- Identify opportunities to improve existing data processes and tools.
- Proactively propose and implement innovative solutions to address data challenges.