Sr Data Engineer

Sr Data Engineer

Requirements

• Strong collaboration, coaching, and peer influencing skills.
• Able to translate complex technical topics into business solutions and strategies as well as turn business requirements into a technical solution.
• Experience implementing statistical methods including hypothesis testing, regression, sample size determination, and analysis of variance. Additional experience building and implementing machine learning algorithms is a plus.
• Experience operating within an Agile framework, including rapid prototyping, learning fast, and scaling to maximize value added.
• Experience with project execution and driving change to core business processes through the innovative use of quantitative techniques.
• Data wrangling experience using MS SQL Server, Oracle SQL Developer, Apache Spark SQL, Snowflake, etc.
• Expertise in programming languages like SQL, Python, etc.
• Experience in Unix and git, automation tools (Autosys, Cron, Airflow, etc.), and AWS Services (i.e. S3, EMR, etc.).
• A track record of staying up to date on emerging analytical and AI trends and driving thought leadership to enhance organizational impact and visibility.
• Bachelor’s degree in computer science, information systems, statistics, or a related field.
• A minimum of 7 years of experience in data engineering is recommended.
• Candidate must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.

Responsibilities

• Support and collaborate with a team of data engineers to create significant improvements for our claim performance analysts, driving more actionable insights for our partners.
• Assist in developing and executing on a multi-year roadmap to automate and augment our analytical process, leveraging the latest analytical tools and passive metric monitoring where possible.
• Work with business-facing analytical engineers to curate new metrics and characteristics in support of ad-hoc partners’ requests and enhance hypothesis testing.
• Contribute to statistical, machine learning, and AI upskilling across the performance analytics team. Develop an understanding of emerging approaches by developing partnerships with key data science and enterprise data partners.
• Coordinate activities with cross-functional IT unit stakeholders (e.g., database, operations, telecommunications, technical support, etc.).
• Support day-to-day responsibilities and ensure progress is made on our strategic investments.
• Collaborate closely with the enterprise data services group’s dedicated team that maintains our data products to prioritize critical enhancements needed to produce better insights.

Preferred Qualifications

• Additional experience building and implementing machine learning algorithms is a plus.