Data Analytics Engineer - Insurance Company
Job Overview
The Data Analytics Engineer will serve as a crucial bridge between our technical data infrastructure and business-focused analytics initiatives. In this role, you'll collaborate with cross-functional teams to transform complex insurance data into actionable insights that drive decision-making across underwriting, claims, pricing, customer experience, and product development. This position offers an exciting opportunity to apply cutting-edge data engineering and analytics techniques to solve real-world insurance challenges.
Key Responsibilities
Data Pipeline Development & Management
- Design, build, and maintain robust data pipelines to collect, process, and analyze insurance data from multiple sources including policy administration systems, claims databases, customer relationship management platforms, and third-party data providers
- Implement efficient ETL/ELT processes to ensure timely and accurate data availability for analytics and reporting purposes
- Optimize data flows and processing methodologies to handle large volumes of insurance-specific data while maintaining performance standards
- Develop automated data quality checks and monitoring systems to ensure data integrity throughout the analytics lifecycle
Analytics & Reporting
- Create and optimize complex SQL queries for insurance-specific data analysis across various business domains
- Develop comprehensive dashboards, reports, and visualization tools using platforms such as Tableau, Power BI, or Looker to communicate insights effectively to stakeholders at all levels
- Generate regular and ad-hoc analytical reports to support business operations and strategic initiatives
- Design and implement self-service analytics capabilities for business users to access relevant insurance metrics and KPIs
Statistical Analysis & Modeling
- Apply statistical methods and techniques to analyze claims patterns, identify risk factors, evaluate pricing models, and detect fraud indicators
- Collaborate with actuaries, underwriters, and data scientists to build and validate predictive models for risk assessment, customer behavior, and other insurance applications
- Implement A/B testing frameworks to evaluate the effectiveness of different approaches to pricing, marketing, and customer engagement
- Develop and maintain statistical models to forecast business metrics such as loss ratios, retention rates, and premium growth
Collaboration & Communication
- Partner with business stakeholders to understand their analytical needs and translate them into technical requirements
- Work closely with IT teams to ensure proper integration of analytics solutions with existing enterprise architecture
- Present findings and recommendations to executive leadership and business teams in clear, actionable terms
- Provide technical guidance and mentorship to junior analytics team members
- Document analytical methodologies, data dictionaries, and solution architectures for knowledge sharing and compliance purposes
Governance & Compliance
- Ensure adherence to data governance policies and regulatory requirements specific to the insurance industry
- Implement data security measures to protect sensitive customer and business information
- Support regulatory reporting requirements including those for state insurance departments, NAIC, and other oversight bodies
- Maintain comprehensive documentation of data lineage and transformations for audit purposes
Required Qualifications
- Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related quantitative field; Master's degree preferred
- 3-5 years of professional experience in data engineering, analytics, or similar roles, with demonstrated progression of responsibilities
- Strong proficiency in SQL and experience with relational database systems (e.g., Oracle, SQL Server, PostgreSQL)
- Hands-on experience with Python, R, or similar programming languages for data manipulation and analysis
- Proven experience building data pipelines and ETL/ELT processes
- Demonstrated expertise with BI and visualization tools such as Tableau, Power BI, Looker, or Qlik
- Solid understanding of data warehousing concepts, dimensional modeling, and analytics best practices
- Experience with big data technologies and cloud-based data platforms (AWS, Azure, GCP)
- Strong analytical thinking and problem-solving skills
- Excellent written and verbal communication abilities, with the capacity to translate technical concepts for non-technical audiences
- Demonstrated ability to manage multiple projects and priorities in a fast-paced environment
Preferred Qualifications
- Insurance industry experience, particularly in property & casualty, life, or health insurance domains
- Understanding of actuarial concepts, underwriting principles, and insurance operations
- Experience with insurance-specific data systems (policy management, claims processing, agency management)
- Knowledge of machine learning techniques and their practical applications in insurance
- Familiarity with NoSQL databases (MongoDB,