About CLARA:

Clara Analytics' mission is to give insurance claims managers the power to improve outcomes dramatically, save millions of dollars, and help thousands of people recover from injuries, recoup damages, and get back on their feet faster after suffering a loss. The opportunities to develop high-value AI and machine learning applications in the insurance industry are nearly unbounded - the sector has only just begun to realize the benefits of adopting these technologies. We are looking for high performers with an entrepreneurial spirit who welcome the challenges and opportunities of thinking big in uncharted territory and are driven to solve challenging problems and develop cutting-edge applications that have a significant impact.

About the role:

CLARA is looking for an experienced Senior Data Engineer who has built data processing systems, data warehouses, and data science supporting ecosystem. They will have strong familiarity working in a cloud environment like AWS or GCP. They will be comfortable in a technical lead role working with other data engineers, application engineers, data scientists, product managers and product delivery teams. This person will be a mentor for the current Data Engineering team.

Key Responsibilities

• Help provide technical leadership in Clara’s data engineering team, driving technology decisions, mentoring others, and contributing significantly on an individual level
• Experience with data tools like AWS Redshift, AWS Sagemaker, AWS Athena/Presto, AWS EMR, and Spark/PySpark
• Use exploration and analytic tools like Apache QuickSight , AWS Athena/Presto, or other BI tools
• Knowledge and experience with Informatica is a plus.
• Build robust data processing pipelines using Airflow, Kubeflow/MLFlow or similar and integrate with multiple components and data sources and sinks
• Design and architect new product features, champion the use of the right cutting edge technologies and tools and mentor the team in the adoption of these new technologies.
• Collaborate with the Data Science and analysts team to ensure that data processing, structure and accessibility maximizes model performance while minimizing costs.
• Work on a bi-weekly sprint schedule in a fast-paced startup environment. Participate in and contribute to scrum meetings i.e. daily stand-up, sprint planning, and retrospectives
• Deliver value in the form of timely, high quality, performant software components and services
• Collaborate with product owners and stakeholders to plan and define requirements

Qualifications & Experience

• Candidates with 7+ years’ experience in software engineering, building large scale systems.
• Experience with the following software/tools is highly desired:
  • Highly proficient with Redshift, RDS,
  • Apache Spark, Hive, etc
  • SQL and NoSQL databases like MySQL, Postgres, DynamoDB, Elasticsearch
  • Workflow management tools like Airflow
  • AWS cloud services: RDS, AWS Lambda, AWS Glue, AWS Athena, EMR (equivalent tools in the GCP stack will also suffice)
• Strong programming skills in at least one of the following languages, Java, Scala, Python and/or C++ accepted.
• Strong analytical skills and advanced SQL knowledge, indexing, query optimization techniques
• Experience implementing software around data processing, metadata management, ETL pipeline tools like Airflow
• Experience working with cross-functional teams in a fast-paced environment
• Experience working with Data Science and Machine Learning Engineerings and ML Ops to build/deploy robust and scalable production systems.
• Ability to translate data needs into detailed functional and technical designs for development, testing and implementation
• Ability to serve as a liaison between technical, quality assurance and non-technical stakeholders throughout the development and deployment process