Director Data Engineering

Dir Data Engineering - GE06AE

We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

We are seeking a highly experienced Director of Engineering to lead our engineering team in developing and maintaining our finance applications.

The team supports various finance applications and processes that are critical to the flow of Financial Transactions inside The Hartford. Transactions from policy & claims admin systems flow through the Finance Pipeline Oracle batch applications for validation, booking, and reporting. The resulting data is consumed by several key business areas including, but not limited to, Actuarial, Finance, Billing, Reinsurance, as well as PL & CL data warehouses. Assets also feature user interfaces for manual premium transactions, correcting errors, and creating dividend transactions.

As the Director of Engineering for Finance Applications, you will oversee the data engineering efforts to design, develop, and maintain robust financial data solutions. You will work closely with cross-functional teams to ensure our applications meet the highest standards of performance, security, and user experience.

Currently the applications are in on prem Oracle with some mainframe footprint and in the middle of cloud journey. This role will be responsible for designing and implementing the future state in cloud. Leverage AI productivity tools to automate manual testing and integrations

Key Responsibilities :

Lead and manage a team of data engineers and analysts, providing technical guidance, mentoring, and career development opportunities.

Perform a comprehensive assessment of existing on-prem Oracle and mainframe systems.

Evaluate current performance, security, and scalability limitations.

The current system relies heavily on manual processes for file testing and bulk updates of reference data, resulting in frequent back-and-forth with customers due to the absence of self-service options. Develop and implement AI solutions to automate validations and integrations, enhancing overall efficiency.

Design a cloud-based architecture utilizing microservices.

Incorporate data mesh or data fabric principles for improved interoperability and scalability.

Establish enterprise standard Reference Data Management (RDM) practices.

Develop a detailed cloud architecture plan, including necessary cloud services and infrastructure.

Design microservices to replace monolithic Oracle and mainframe systems.

Ensure compliance with security and performance standards.

Create a detailed migration plan, prioritizing critical applications and data.

Lead and manage the engineering team responsible for finance applications.

Collaborate with product management, finance, and other departments to align engineering projects with business objectives.

Establish and enforce engineering best practices, standards, and processes.

Monitor and evaluate the performance of engineering projects and teams.

Provide technical guidance and mentorship to engineering staff.

Manage the engineering department's budget and resource allocation.

Stay up-to-date with industry trends and emerging technologies to drive innovation.

Ensure compliance with regulatory requirements and industry standards.

Be a thought leader, driving positive change and simplification while improving delivery speed.

Qualifications :

Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

10+ years of experience in data engineering, with at least 2 years focused on generative AI technologies.

Extensive experience in data engineering, with a focus on financial applications.

Proven track record of leading and managing data engineering teams and modernization experience.

Strong experience in implementing production-ready enterprise-grade GenAI pipelines.

Experience with prompt engineering techniques for large language models.

Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.

Strong understanding of financial systems, processes, and regulations.

Proficiency in programming languages and technologies related to data engineering (e.g., Spark, Scala, Python, SQL, Informatica, Snowflake, Big Query etc.).

Experience with cloud platforms (e.g., AWS, GCP) and microservices architecture.

Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).

Excellent problem-solving and analytical skills.

Strong communication and leadership abilities.

Ability to work collaboratively with cross-functional teams.

Preferred Experience :

Expertise in Next Gen ETL technologies and programming (SQL, No SQL, Spark scala / python, Big Query, Snowflake etc.)

Managing backend data eco systems for finance applications.

Experienced , Innovative and driven to modernize an on-prem critical application.

Gen AI data engineering and automation experience.

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.

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is :

$156,000 - $234,000

Equal Opportunity Employer / Sex / Race / Color / Veterans / Disability / Sexual Orientation / Gender Identity or Expression / Religion / Age

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