Senior Data Management Engineer

NextEra Energy is the world's largest producer of wind and solar energy. With operations in nearly all 50 states and four provinces in Canada, our nearly 15,000 employees are committed to finding innovative, industry-leading solutions to provide safe, reliable and affordable clean energy to millions of customers throughout North America. We are leading the decarbonization of the U.S. economy with our goal to reach Real Zero carbon emissions from our operations by 2045 while improving customer affordability and reliability. Do you want to help us achieve Real Zero? Join our world-class team today. Learn more.

 

Position Specific Description

 

As a Senior Data Management Engineer at Palms Insurance, you will play a critical role in designing, building, and managing the data infrastructure and pipelines that support our analytics and data science initiatives. This position requires a highly skilled individual with extensive experience in data engineering and a strong understanding of risk management, finance, and commercial insurance. The ideal candidate will be proficient in creating robust ETL processes, ensuring data quality, and optimizing data flow, while also contributing to the organization's strategic data initiatives. The role involves significant collaboration with data scientists, analysts, and business stakeholders. Additionally, experience with Scrum, documentation and repository maintenance, and integration with tools such as GitHub and JIRA are essential.

 

Data Engineering and Infrastructure:
•    Co-develop and maintain a comprehensive data architecture in collaboration with the Head of Data Analytics and other stakeholders.
•    Collaborate with data scientists and analysts to support the development of machine learning models and advanced analytics solutions.
•    Oversee the release and integration of data engineering solutions into production environments.
•    Design, develop, and manage ETL processes to facilitate the extraction, transformation, and loading of data from various sources.
•    Ensure the scalability, reliability, and performance of data pipelines and storage solutions.
•    Implement data quality and validation processes to maintain data integrity and accuracy.
•    Optimize data architecture for efficient access and processing, supporting both batch and real-time data needs.
•    Maintain version control and continuous integration/deployment (CI/CD) pipelines using GitHub and other tools.

 

Innovation and Continuous Improvement:
•    Stay updated on the latest industry trends, technologies, and best practices in data engineering.
•    Evaluate and adopt new tools and technologies to enhance data infrastructure and engineering capabilities.
•    Drive innovation by continuously improving existing data processes, models, and frameworks.
•    Participate in peer code reviews to ensure high-quality and reliable data engineering work.

 

Collaboration and Communication:
•    Work closely with stakeholders across finance, underwriting, claims, and actuarial departments to understand their data needs and provide effective solutions.
•    Effectively communicate complex technical concepts to non-technical audiences, including senior leadership.
•    Develop strong relationships with external partners and vendors to enhance data engineering capabilities.
•    Utilize Scrum methodologies to manage projects, ensuring timely delivery aligned with business objectives.

 

Governance and Compliance:
•    Ensure data engineering activities comply with industry regulations and company policies.
•    Implement data governance best practices to maintain data integrity, quality, and security.
•    Develop and oversee standards, guidelines, and processes for data management and engineering.

 

The ideal candidate will meet the following qualifications:

 

Education & Experience:
Master’s degree in Computer Science, Engineering, Information Systems, or a related field.

 

Technical Skills:
•    Expert knowledge in data engineering, ETL processes, Rest API, and exploratory data analysis.
•    Strong in programming languages such as SQL (CTE’s, Stored Procedures) and Python with parallel computation (Dask)
•    Experience with AWS infrastructures (e.g., Glue, Lamda, CloudWatch, Redshift, EC2, S3, SNS, Aurora).
•    Reporting tools (PowerBI, and Flask or Quarto), and DevOps tools (Terraform, Docker, Snowflake).
•    Strong experience with data warehousing solutions and architectural design.
•    Proficiency in GitHub integration with JIRA for project tracking, version control with GitLab actions.
•    Strong Scrum skills for managing projects in a fast-pac