Principal Data Analytics Engineer

Tower Hill Insurance Group

Principal Data Analytics Engineer responsible for leading data initiatives and collaborating with business stakeholders at Tower Hill Insurance Group. Focused on data engineering and analytics for impactful solutions.

Posted 4/28/2026full-timeConnecticut, Florida, Iowa, Kentucky, Mississippi, Missouri, North Carolina, Ohio, South Carolina, Tennessee, Texas, Utah, Virginia, West Virginia • 🇺🇸 United StatesLeadWebsite

Tech Stack

Tools & technologies

AirflowApacheAWSAzureCloudDockerETLGrafanaJenkinsKafkaKubernetesPandasPythonRPATerraformVault

About the role

Key responsibilities & impact

Lead the end-to-end delivery of complex data engineering projects, including requirements definition with business stakeholders, technical design, implementation oversight, and delivery coordination with data engineering, analytics, and AI/ML teams
Serve as the primary technical liaison between business partners and engineering teams, translating business requirements into well-scoped, executable data initiatives with clear outcomes
Architect and develop cloud-native data solutions on AWS, including the design and deployment of data pipelines using AWS Glue, Airflow (Amazon MWAA), Step Functions, Lambda, and related services
Lead the migration and modernization of existing data workflows, including the conversion of RPA-based automation into cloud-native orchestration solutions using AWS Airflow
Design, develop, and deploy RESTful and authenticated APIs on Kubernetes (K8s) to expose data services and other reusable data products consumed by downstream systems
Oversee and contribute to infrastructure-as-code practices using Terraform, ensuring analytics and data engineering workloads are provisioned, managed, and repeatable across environments
Establish and enforce data pipeline best practices including data quality checks, lineage tracking, and governance standards across all projects under this role's scope
Monitor, observe, and maintain production data systems and pipelines, using tools such as CloudWatch, DataDog, or Grafana as applicable
Conduct exploratory and operational data analysis to surface deficiencies, validate pipeline outputs, and support data-driven decision making for business stakeholders
Define and communicate data architecture standards and patterns to both technical and non-technical audiences, including documentation of architectural decisions and pipeline design
Collaborate on cross-cutting concerns such as data security, infrastructure alignment, and platform strategy
Coordinate with DevOps and infrastructure teams to ensure that data engineering deliverables align with CI/CD pipelines, containerization standards, and broader organizational engineering practices

Requirements

What you’ll need

High School Diploma or GED required
Bachelor’s Degree in Computer Science or related field preferred
Minimum of seven (7) to ten (10) years of relevant work experience required in data engineering, analytics, or automation required
Advanced Python programming skills for data engineering, automation, and analytics including: data manipulation (pandas, polars), AWS SDK integration (boto3), database connectivity (SQLAlchemy, psycopg2), workflow orchestration (Apache Airflow providers), API development (FastAPI), data validation (Pydantic, Great Expectations), testing frameworks, and async programming for high-performance applications
Deep expertise with Apache Airflow and AWS Managed Workflows for Apache Airflow (MWAA), including DAG development, scheduling strategies, and operational best practices
Strong proficiency with AWS data services including Glue (ETL, Data Catalog, Crawlers), S3, Athena, Lambda, Step Functions, and EventBridge
Experience with Infrastructure as Code (Terraform, CloudFormation) and CI/CD tools (GitHub Actions, Azure DevOps, Jenkins) is highly preferred
Working knowledge of containerization (Docker) and orchestration (ECS, Kubernetes) for data workloads
Experience implementing security frameworks and best practices for API development including authentication/authorization (OAuth 2.0, JWT, SAML), API gateway security, secrets management (AWS Secrets Manager, Vault), encryption (TLS/SSL, at-rest encryption), rate limiting, and compliance with standards (OWASP API Security Top 10, SOC 2)
Experience with Microsoft Power Platform, specifically Power Automate (including Desktop flows for UI automation) and Power Apps or RPA platforms such as UiPath
Experience with real-time data streaming platforms such as Kinesis, Kafka, or Flink.
AWS Certified Solutions Architect Professional and / or AWS Data Analytics – Specialty is preferred
Valid Driver’s License required

Benefits

Comp & perks

Medical
Dental
Vision
Life & Disability Insurance
401(k)
Health Savings Account
Accident, Critical Illness and Hospital Indemnity
Pet insurance
Paid time off & Holiday pay

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Pythondata manipulationAWS SDKSQLAlchemyApache AirflowRESTful APIsTerraformdata validationcontainerizationreal-time data streaming

Soft Skills

communicationcollaborationleadershipproblem-solvingtechnical liaisondocumentationdata-driven decision makingproject managementrequirements definitionbest practices enforcement

Certifications

AWS Certified Solutions Architect ProfessionalAWS Data Analytics – Specialty