Data Analytics Engineer

Job Type Full-time Description

Tower Hill Insurance Group has an exciting opportunity for a talented Data Analytics Engineer who enjoys intellectual challenges and is seeking a rewarding career with a company that is experiencing growth. Not only is Tower Hill Insurance one of Florida's most trusted names in homeowners insurance, but it offers great opportunities for career advancement and personal growth, along with very competitive benefits and rewards. We are growing at a consistent pace and seek professional individuals with drive, team mentality, who want to make an impact, and are committed to a long-term career in the insurance industry.   

The Data Analytics Engineer drives the design and implementation of a high-performance data ecosystem to support analytics, enable AI/ML, and other system functions. This position also analyzes data and collaborates with internal stakeholders to identify opportunities for improvement. This role leverages the team’s deep expertise in data engineering, data science, advanced analytics, and insurance industry data to aid business partners in risk management, drive efficiencies, and improve customer experience.

ESSENTIAL DUTIES AND RESPONSIBILITIES

· Design and implement end-to-end scalable data pipelines in the cloud, supporting both production and analytic use cases using AWS services.

· Partner with internal product owners, data scientists, and ML engineers to help define requirements and outcomes for data-focused initiatives.

· Develop comprehensive architectural documentation and communicate data architecture principles to both technical and non-technical stakeholders.

· Conduct exploratory data analysis to reveal deficiencies and opportunities with tangible evidence.

· Ensure data governance practices are adopted, data quality checks, and data lineage implemented in the data pipeline.

ADDITIONAL DUTIES

This job description reflects the general duties considered necessary to describe the essential functions of the job and should not be considered a complete description of all the work requirements and expectations of the position. Tower Hill reserves the right to assign duties not listed herein as necessary to accomplish the goals of the organization.

Requirements

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

EDUCATION 

High School Diploma or GED required. Bachelor’s Degree in Computer Science, Statistics, Mathematics, Engineering, or related field preferred.

EXPERIENCE 

Minimum of five (5) years of relevant work experience in data engineering and data architecture required, including the following: 

· Minimum of two (2) years of experience in cloud computing (AWS, Azure or Google Cloud).

· Strong programming skills in SQL and Python with experience using PySpark and Pandas for large-scale data processing to clean, transform, and integrate data from multiple sources into unified datasets. 

· Strong analytical skills with the ability to work on semi-structured and unstructured datasets along with problem solving and troubleshooting maturity.

The following work experience is highly preferred: 

· Hands-on deep experience with AWS data engineering stack including Glue ETL, EMR, Lambda, Step Functions, RDS, DynamoDB, Redis, ElasticSearch, and S3 to develop and orchestrate serverless workflows comprising scalable and reliable data pipelines.

· Experience with API management, including design, implementation, and monitoring. 

· Ability to construct batch and streaming microservices exposed as REST, gRPC and/or GraphQL endpoints with tools like Flask and FastAPI.

· Experience designing and implementing event-based stream processing solutions, using technologies such as Kafka, Kinesis, Spark and Flink.

· Experience with version control using git in a collaborative team setting with understanding of branching strategies. Familiarity with DevOps practices including CI/CD pipelines, containerization, and infrastructure as code (e.g., Docker, Kubernetes, Terraform, Jenkins). 

· Experience with monitoring and observability of applications and systems using logs and metrics (tools and dashboards). 

· Experience setting up and using Kibana, Grafana, Splunk, DataDog, etc.is a plus.

CERTIFICATIONS

AWS Certifications in AI or ML preferred. 

LICENSES

Valid Driver’s License required.

 

Prefer