Using proprietary algorithms and proven AI, Carpe Data harnesses the power of emerging and alternative data for insurance carriers around the globe. Utilizing Carpe Data’s data, insurers gain deeper insight into risks and significantly enhance many aspects of the insurance life cycle, including underwriting, claims, and book assessment.

You will advance our efforts to build high quality data products that fulfill our goal of "data as a core competency" within Carpe Data's cutting edge Big Data pipelines. The key to success in this role is the ability to identify areas for improvement with our existing methods and utilizing your technical skills to resolve them. You will have the chance to exercise your creativity in an ETL process through iterative testing and analysis and your purview will include all facets of our data lifecycle, from data ingestion processes to data quality monitoring strategies. You will work closely with other Data Analysts and our Development teams, with Product as key stakeholders.

Responsibilities

• Translate stakeholder feedback relating to quality of existing products or the possibility of new products or approaches into a tactical plan
• Drive efficiency and automation throughout our data processes and workflows
• Establish and monitor critical data metrics and provide reports to technical and executive leadership
• Determine product impact for data quality issues and propose solutions
• Evaluate our datastores across dimensions such as completeness, accuracy and quality
• Interface with Developers to correct data quality issues
• Augment existing data assessment techniques
• Exploratory projects where you are given a broad hypothesis and are asked to arrive at a conclusion

Skills And Experience For Success In This Role

• Proven expertise in automation tools and frameworks, including proficiency in dbt & Airflow
• Ability to drive efficiency, enhance data processing workflows to optimize pipelines
• SQL expert
• Experience with ETL processes and Big Data pipelines
• 3+ years experience with large dataset assessments
• Command of at least one server side programming language. Ideally Python/Scala
• Experience with AWS, Snowflake, Sigma, or like solutions
• Thorough understanding of all complex data types - structs, arrays, etc
• Understanding of end to end orchestration techniques and tools is a plus
• Experience managing data analysts is a plus
• Involvement in data cataloging, data lineage and data governance is a plus