Technical Lead

Job Summary
This hybrid day shift role is for a seasoned technical lead with deep hands on experience in Azure Data Factory and Databricks guiding complex data engineering initiatives for an international organization. The role focuses on architecting robust data pipelines and analytics solutions mentoring technical teams and collaborating with business stakeholders. Experience in life and annuities insurance is preferred to enhance domain driven design and insight generation across enterprise data plat
Responsibilities
Drive end to end design and implementation of scalable data pipelines using Azure Data Factory and Databricks to support enterprise analytics and reporting needs across the organization
Lead technical solutioning for complex data integration scenarios by defining patterns for ingestion transformation and orchestration that ensure reliability performance and maintainability
Coordinate hybrid model delivery activities by planning onsite and remote work schedules that optimize collaboration with cross functional partners and maintain consistent progress on critical milestones
Provide technical guidance to data engineers and developers by reviewing code design artifacts and deployment approaches to uphold high standards of quality security and operational stability
Collaborate with business and product stakeholders by translating analytical and reporting requirements into well structured Azure based data solutions that deliver measurable value to customers and internal teams
Optimize Databricks workloads by tuning clusters jobs and queries to improve cost efficiency execution speed and resource utilization while enforcing best practices for workspace organization and governance
Implement robust monitoring logging and alerting for Azure Data Factory and Databricks jobs by leveraging native tools and dashboards to proactively identify issues and reduce downtime
Ensure data quality and consistency across data pipelines by designing validation rules reconciliation checks and error handling strategies that strengthen trust in curated datasets and downstream analytics
Coordinate secure data access and compliance alignment by working with security and risk partners to apply appropriate controls masking and role based permissions across data platforms
Support project planning and estimation activities by providing realistic effort assessments for data engineering tasks enabling accurate timelines and resource allocation for delivery teams
Partner with architecture and infrastructure groups by aligning solutions with enterprise standards reference architectures and cloud governance guidelines to maintain long term sustainability
Contribute to continuous improvement initiatives by capturing lessons learned researching emerging Azure data services and proposing enhancements that increase productivity and innovation across projects
Engage with domain experts in life and annuities insurance when available by shaping data models metrics and analytics that reflect key business processes and improve decision making for policy and claims outcomes
Qualifications
Demonstrate extensive hands on expertise with Azure Data Factory including pipeline development data flow configurations and integration runtime management for complex enterprise workloads
Apply strong Databricks knowledge by building performant notebooks jobs and workflows that leverage Spark based processing for batch and near real time data transformation scenarios
Bring proven experience in designing cloud data architectures that include storage choices compute strategies and integration patterns aligned with organizational standards and performance expectations
Utilize solid data engineering fundamentals such as modeling ETL design optimization and testing to create resilient data solutions that are easy to maintain and extend over time
Leverage any background in life and annuities insurance to interpret business concepts such as policy lifecycle underwriting claims and actuarial analysis when designing data structures and analytics outputs
Communicate effectively with technical and nontechnical partners by explaining solution approaches dependencies and risks in clear language that supports informed decisions and collaborative planning
Operate comfortably in a hybrid work environment by using collaboration tools disciplined documentation and regular touchpoints to maintain transparency and alignment across onsite and remote participants
Certifications Required
Azure Data Engineer Associate or equivalent cloud data certification preferred

Work arrangement
Hybrid