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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in SQL and Python for data extraction and manipulation, with a strong focus on data quality and governance. Proven ability to lead projects, collaborate with stakeholders, and implement process improvements in data engineering environments.
Highest-signal resume keywords
SQL Data QueryingPython Data EngineeringAWS Data TechnologiesData Pipeline OptimizationData Quality Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonData Pipeline DevelopmentData TransformationData ValidationData GovernanceData AnalysisBatch ProcessingAutomation of Data WorkflowsData Documentation
Soft Skills
Analytical SkillsProblem-SolvingAttention to DetailCommunication SkillsProactive Approach
Tools & Technologies
AWS GlueCloud-Native ServicesData Engineering Platforms
Industry Keywords
InsuranceFinancial ServicesData-Intensive Industry
Tech Stack
Tools & technologiesAWSCloudPythonSQL
About the role
Key responsibilities & impact- Lead customer underwriting proof-of-concept projects from initial request through final delivery
- Work with customer-provided address data and match it to unique reference identifiers
- Extract, transform, and deliver risk intelligence data, including flood, fire, and burglary risk factors
- Produce clear data outputs and supporting documentation, including data dictionaries
- Investigate data-quality questions, coverage issues, and customer queries
- Use SQL and Python to extract, manipulate, validate, and prepare complex datasets
- Collaborate with internal stakeholders to understand evolving business and customer requirements
- Support and enhance underwriting data platforms and associated data processes
- Share knowledge and provide cross-functional support to reduce single-person dependencies
- Identify opportunities to automate manual activities within the proof-of-concept lifecycle
- Leverage AWS technologies to improve scalability, efficiency, and repeatability of data processes
- Contribute recommendations that improve team effectiveness, data quality, and customer experience
- Maintain technical documentation and provide project updates to stakeholders
Requirements
What you’ll need- Strong SQL skills with experience querying and manipulating large datasets
- Strong Python experience in a data engineering environment
- Experience building, maintaining, or optimizing data pipelines and data processes
- Experience working with AWS data engineering technologies
- Understanding of data quality, validation, and governance practices
- Strong analytical and problem-solving skills
- Excellent attention to detail
- Ability to communicate complex technical concepts clearly and confidently
- Experience working with both technical and non-technical stakeholders
- Proactive approach to identifying and implementing process improvements
- Ability to manage priorities and deliver work in a fast-paced environment
- Preferred: experience with AWS Glue
- Preferred: experience deploying Python-based data engineering workloads into production environments
- Preferred: experience automating data workflows using cloud-native services
- Preferred: understanding of batch processing, scheduling, and scalable data solutions
- Preferred: experience within insurance, financial services, or another data-intensive industry
Benefits
Comp & perks- Short-term incentive opportunity
- Medical coverage
- Life insurance
- Pension plan
- Paid time off in line with local labor laws
- Wellness initiatives
- Fitness programs
- Team-building activities
- Career development opportunities
- Collaborative, people-first culture