Remote
This role does not support visa‑dependent candidates currently or in the foreseeable future.”
Job Summary
Senior developer within a hybrid working data engineering team designing and implementing scalable data solutions using Python PySpark Databricks and Amazon S3 for an international organization. Contribute hands on expertise to build reliable data pipelines and optimize Delta Lake based platforms that power analytics innovation and responsible data driven decisions across the enterprise.
Responsibilities
- Design and implement robust data pipelines using Databricks Workflows PySpark and Databricks SQL so that large scale data processing runs reliably for business critical analytics tasks.
- Develop efficient data ingestion and extraction solutions that integrate Amazon S3 with Databricks environments so that data assets remain accurate timely and easy to consume.
- Optimize Databricks Delta Lake architectures including partitioning and clustering strategies so that query performance improves and storage costs remain controlled.
- Build reusable Python modules and utilities that standardize data transformations so that multiple teams can adopt consistent and maintainable engineering practices.
- Configure and monitor scheduled jobs in Databricks Workflows so that dependencies retries and alerts are managed effectively for day shift operations.
- Implement rigorous data quality checks validation rules and reconciliation processes so that downstream reporting and machine learning models rely on trustworthy datasets.
- Collaborate with data analysts and product stakeholders in a hybrid work model so that requirements are clearly translated into technical designs and delivered solutions match expectations.
- Document technical designs coding standards and operational runbooks in clear language so that future maintenance and onboarding are simplified for global team members.
- Troubleshoot performance bottlenecks in PySpark jobs and Databricks SQL queries so that processing windows are reduced and service level objectives are consistently met.
- Apply secure coding and data handling practices across S3 buckets secrets management and Databricks configurations so that regulatory and organizational compliance goals are supported.
- Contribute to continuous improvement initiatives such as refactoring legacy pipelines into Delta Lake patterns so that the platform remains modern efficient and easier to extend.
- Coordinate with platform engineers and architects when introducing new features or version upgrades so that changes are aligned with enterprise standards and long term strategy.
- Mentor peers through code reviews knowledge sharing sessions and constructive feedback so that team capability grows and delivery quality remains high.
Qualifications
- Bring eight to twelve years of hands on software or data engineering experience with proven delivery of large scale data processing solutions in an enterprise environment.
- Demonstrate advanced proficiency in Python and PySpark including writing modular code handling complex transformations and optimizing jobs for distributed execution.
- Show practical expertise with Amazon S3 for data storage lifecycle management and secure integration with analytics platforms used in global organizations.
- Offer strong experience with Databricks SQL for building curated views reusable queries and performant datasets that serve reporting and dashboard needs.
- Exhibit deep understanding of Databricks Delta Lake concepts such as transaction logs time travel and schema evolution to maintain reliable analytical tables.
- Display experience configuring Databricks Workflows including job orchestration parameterization and alerting in a hybrid work setting without travel obligations.
- Possess familiarity with version control tools testing frameworks and continuous integration practices that keep data engineering codebases stable and auditable.
- Value collaborative communication skills that enable effective interaction with cross functional partners across different regions and time zones within a day shift schedule.
Employee Benefits
Cognizant offers a competitive and comprehensive benefits package, including:
- Medical, dental, and vision insurance
- Paid time off, holidays, and parental leave
- Life and disability insurance
- Employee assistance and wellness programs
- Learning, certification, and career development opportunities
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
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。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
