Job Summary
Drive complex data engineering and analytics solutions as a senior developer within a hybrid work model using Python Databricks SQL Databricks Workflows and PySpark to build scalable data pipelines and optimize data platforms. Collaborate with cross functional teams to deliver reliable insights improve system performance and support business decision making in a global enterprise environment.
Responsibilities
- Design and implement robust data pipelines using Python and PySpark to ingest transform and validate large scale structured and unstructured datasets in Databricks environments.
- Optimize Databricks SQL queries and data models to ensure efficient analytics performance reduced compute costs and fast delivery of insights to business stakeholders.
- Configure and manage Databricks Workflows to orchestrate complex end to end data processes including scheduling dependency handling and monitoring for reliability.
- Collaborate closely with data analysts and business partners to translate analytical requirements into maintainable technical solutions that directly support strategic objectives.
- Implement comprehensive data quality checks error handling and logging within Python and PySpark jobs to improve reliability observability and trust in delivered data products.
- Conduct performance tuning of PySpark jobs and Databricks SQL workloads to maximize resource utilization and minimize processing times across production and nonproduction environments.
- Apply secure coding and data handling practices within Databricks to protect sensitive information and comply with enterprise data governance policies and regulatory expectations.
- Review existing data workflows and pipelines to identify opportunities for simplification automation and standardization that reduce operational effort and improve scalability.
- Provide detailed technical documentation for data pipelines job configurations and workflow dependencies so that support teams and peers can easily maintain and enhance solutions.
- Support incident resolution and root cause analysis for data pipeline failures or performance degradations implementing preventive improvements for long term stability.
- Coordinate with platform and infrastructure teams to align Databricks cluster configurations libraries and integrations with evolving enterprise standards and best practices.
- Guide junior developers and peers through code reviews and knowledge sharing sessions focused on Python PySpark and Databricks usage improving overall team capability.
- Engage in continuous improvement activities by evaluating emerging Databricks features and Python ecosystem tools that can increase efficiency and expand analytics possibilities.
Qualifications
- Demonstrate strong proficiency in Python programming including modular design unit testing and effective use of data processing libraries in enterprise solutions.
- Exhibit advanced experience with PySpark for distributed data processing including working with large datasets optimizing transformations and managing performance.
- Show deep hands on expertise in Databricks SQL including writing complex queries building reusable views and tuning execution plans for analytic workloads.
- Apply practical experience configuring and operating Databricks Workflows for orchestration of production pipelines including job parameterization and monitoring.
- Display solid understanding of data warehousing concepts data modeling principles and relational database practices that underpin high quality analytics solutions.
- Demonstrate experience working in hybrid work models effectively collaborating through digital tools and coordinating onsite engagement as required by project work.
- Utilize strong problem solving skills and attention to detail to troubleshoot data and performance issues ensuring accurate and timely delivery of information to stakeholders.
Salary and Other Compensation:
The annual salary for this position is between $70-75K depending on experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
· Medical/Dental/Vision/Life Insurance
· Paid holidays plus Paid Time Off
· 401(k) plan and contributions
· Long-term/Short-term Disability
· Paid Parental Leave
· Employee Stock Purchase Plan
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 la
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。
