Sr. Developer

• 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