Job Summary
Serve as a senior developer specializing in Databricks and PySpark to design build and optimize large scale data and analytics solutions in a hybrid work environment using prompt engineering to enable intelligent data products supporting day shift operations without travel and delivering measurable value to business stakeholders and society through data driven outcomes.
Responsibilities
Design and develop scalable data pipelines on Databricks using PySpark and Databricks SQL to deliver reliable and timely data for analytics and reporting needs.Implement robust data transformation logic in Databricks Workflows to ensure consistent data quality and alignment with business rules across multiple domains.Configure and optimize Databricks CLI based automation scripts to streamline environment setup deployment and operational tasks for data engineering projects.Apply prompt engineering techniques to build and refine intelligent data solutions that improve insight discovery and decision support for business teams.Tune PySpark jobs and Databricks SQL queries to improve performance manage costs and ensure efficient use of compute resources across the data platform.Collaborate with data architects analysts and product teams in a hybrid work setup to translate complex requirements into clear maintainable Databricks based solutions.Establish monitoring logging and alerting practices for Databricks Workflows to ensure high reliability rapid incident detection and swift remediation.Document data models transformation logic and operational runbooks so that project teams can understand support and extend delivered solutions with confidence.Ensure all data solutions comply with security and privacy standards so that sensitive information is protected while enabling responsible insight generation.Mentor junior developers in Databricks PySpark and prompt engineering techniques so that the team continually improves its technical depth and delivery quality.Partner with business stakeholders to validate outputs from Databricks SQL dashboards and models so that delivered insights remain accurate relevant and actionable.Drive continuous improvement of development practices using Databricks CLI and version control so that releases remain predictable traceable and low risk.Contribute to innovative use cases that leverage Databricks and prompt engineering to generate positive business value and broader societal impact through better use of data.
Qualifications
Demonstrate eight to twelve years of progressive experience in data engineering or development roles with a strong recent focus on Databricks based solutions.Show advanced hands on expertise in PySpark and Databricks SQL for building complex data transformations aggregations and analytical data sets.Exhibit solid experience configuring and using Databricks Workflows to orchestrate data pipelines manage dependencies and schedule production workloads.Display practical proficiency with Databricks CLI for automation of environment management job deployment and configuration tasks in enterprise settings.Apply working knowledge of prompt engineering concepts to design effective prompts that enhance data exploration insight generation and analytics workflows.Possess strong skills in writing clean maintainable code using version control and code review practices that support high quality and collaborative delivery.Bring proven experience working in hybrid teams and day shift schedules while maintaining clear communication accountability and focus on shared objectives.
Certifications Required
Databricks Certified Data Engineer Professional or equivalent advanced Databricks certification is preferred for this role.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
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