Director, Data Engineering Personal Lines Lead

2 weeks ago

The Loop, Australia The Hartford Full time

Director Data Engineering - GE06AE

We take pride in being more than just an insurance company that provides coverages and policies. Join us to work towards your goals and help others achieve theirs. Become part of our team that is shaping the future.

The Hartford is in search of a Director and Data Engineer to lead a team of data engineers within Actuarial. In this role, you will be responsible for designing, developing, and implementing sustainable data assets to support machine learning and artificial intelligence initiatives across various strategic projects.

This position is part of a specialized actuarial/data science team that focuses on enhancing core actuarial processes through statistical modeling, machine learning, cloud computing, and big data platforms. The team's work includes modeling for pricing, class plans, and profitability. The Director will oversee the implementation of data models and MLOps pipelines for actuarial models in Personal Lines.

As a Director and Data Engineer, you will be involved in the entire software development lifecycle process, supporting continuous data delivery while staying abreast of emerging technologies. This role offers exposure to the latest data technologies, software engineering practices, MLOPs, Agile delivery frameworks, and a focus on delivering innovative solutions that drive business value. Collaboration, self-organization, and visibility are key within this forward-thinking organization.

The Director Data Engineering role offers a Hybrid work arrangement, requiring office presence in Hartford, CT; Charlotte, NC; Chicago, IL; Columbus, OH, three days a week (Tuesday through Thursday).

Responsibilities:

  • Collaborate with Data Scientists and Product Owners to recommend strategies for business opportunities.
  • Develop and implement design for data pipelines and testing frameworks, focusing on maintainability, reliability, security, and scalability.
  • Identify and validate internal and external data sources, working with Subject Matter Experts to assess data lineage and suitability for use cases.
  • Guide data warehouses and data architectures, merging disparate data sources to ensure quality and relevance of data solutions.
  • Lead use of GitHub best practices for version control, documentation, and code collaboration in the data science lifecycle.
  • Contribute to a roadmap for building enterprise-grade data assets and leveraging cloud-based technologies.
  • Drive innovation with a focus on delivering results, customer adoption, and continuous improvement.
  • Coordinate activities with cross-functional IT stakeholders.

Qualifications:

  • 8+ years of experience in Data Engineering.
  • Bachelor's degree in Computer Science, Engineering, IT, MIS, or related discipline.
  • Expertise in Python, SQL, and R.
  • Proficiency in data ingestion from various sources including relational databases, Hadoop/Spark, cloud data sources, XML, JSON.
  • Skills in ETL, metadata management, data validation, Unix, and Git.
  • Experience with Automation tools (Autosys, Cron, Airflow, etc.).
  • Knowledge of AWS Services (e.g., S3, EMR) and Cloud data warehouses (e.g., Snowflake, Redshift) is advantageous.
  • Effective communication with technical and non-technical teams.
  • Ability to translate complex technical topics into business solutions and strategies.
  • Experience leading project execution and driving change in core business processes through quantitative techniques.

Compensation:

The annualized base pay range is determined based on market analysis. Actual base pay may vary based on factors including performance and proficiency. Base pay is just one component of the total compensation package, which may include bonuses, incentives, and recognition. The annualized base pay range for this role is withheld.

About Us | Culture & Employee Insights | Diversity, Equity and Inclusion | Benefits

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