Job Summary
This hybrid role seeks a senior developer with six to eight years of experience specializing in Databricks SQL Databricks Workflows and PySpark to build and optimize data solutions for life and annuities insurance. The role focuses on scalable pipelines reliable analytics and insight delivery that improve policyholder outcomes and support responsible business decisions.
Responsibilities
Design build and optimize Databricks SQL queries that support complex life and annuities insurance reporting and analytics needs while ensuring accuracy and performance
Develop robust PySpark based data pipelines that process large insurance datasets efficiently and reliably for downstream actuarial and operational use
Configure and maintain Databricks Workflows that orchestrate end to end data processing and analytics tasks across hybrid environments with predictable execution
Implement data quality checks and validation rules tailored to life and annuities products so that policy claim and premium data remains consistent and trusted
Collaborate with business analysts and actuaries to translate life and annuities requirements into scalable Databricks solutions that enable data driven decisions
Optimize storage formats partitioning strategies and cluster configurations in Databricks to balance cost performance and reliability for large insurance workloads
Create clear technical documentation that explains data models transformation logic and workflow behavior in language that is understandable across technology and insurance teams
Support day to day production operations by investigating incidents resolving data issues and implementing preventive improvements that reduce recurring problems
Apply secure coding and data handling practices so that sensitive insurance data is protected in line with enterprise governance and regulatory expectations
Coordinate with hybrid infrastructure and platform teams to ensure Databricks environments connectivity and dependencies are stable for day shift operations
Participate in sprint activities by estimating effort planning tasks and delivering high quality development outcomes aligned with agreed timelines
Engage with testing teams to define test data scenarios and acceptance criteria that reflect real life and annuities processes and edge cases
Contribute to continuous improvement by identifying opportunities to streamline workflows reduce manual steps and enhance analytics capabilities for business stakeholders
Qualifications
Possess professional experience of six to eight years in data engineering or development roles with a strong focus on Databricks SQL and PySpark within enterprise settings
Demonstrate hands on expertise in configuring and managing Databricks Workflows for complex multi step data and analytics processes in a hybrid work model
Show deep domain understanding of life and annuities insurance concepts including policy lifecycle premiums claims reserves and related data structures
Exhibit strong proficiency in writing efficient PySpark code tuning transformations and handling large scale structured and semi structured datasets
Bring practical knowledge of relational databases data warehousing and dimensional modeling techniques that support insurance reporting and analytics
Display familiarity with data governance concepts such as data lineage metadata management and access control in regulated industries like insurance
Communicate clearly with cross functional teams documenting solutions and explaining technical decisions in terms that align with business outcomes
Certifications Required
Preferred certifications include Databricks Data Engineer Associate and relevant insurance or actuarial domain certifications.
