Job Summary
This hybrid role is for a seasoned Technical Lead with strong hands on expertise in PySpark Python and Azure Databricks responsible for designing scalable data solutions guiding technical implementation and ensuring high quality delivery in a day shift environment while collaborating with cross functional teams to support critical airline and enterprise analytics use cases with measurable business impact.
Responsibilities
- Design robust data engineering solutions using PySpark and Python that efficiently process large scale datasets and meet strict performance expectations for business critical analytics
- Develop reusable and optimized data pipelines on Azure Databricks that support batch and near real time processing while maintaining high standards of reliability and observability
- Coordinate with product owners and business partners to translate complex analytical needs into clear technical designs that align with enterprise data architecture strategies
- Oversee code reviews and enforce engineering best practices that improve code readability maintainability and long term sustainability across multiple project teams
- Guide the selection and configuration of Azure Databricks clusters and related Azure services to balance cost performance scalability and operational resilience
- Implement rigorous testing strategies including unit integration and regression tests that ensure data accuracy and stability across evolving data sources and transformations
- Monitor production data pipelines proactively using dashboards and alerts to quickly identify issues reduce downtime and protect stakeholder confidence in analytics outputs
- Collaborate closely with data scientists analysts and domain experts to deliver curated data products that accelerate experimentation and support airline and enterprise decision making
- Drive continuous improvement of development workflows by refining version control branching strategies and deployment automation for Azure Databricks based solutions
- Document solution designs data models and operational procedures in a clear and comprehensive manner that supports knowledge sharing and onboarding of new team members
- Coordinate with security and compliance partners to implement data protection policies and ensure that all data solutions adhere to enterprise governance and regulatory requirements
- Optimize Spark jobs by tuning partitions caching and resource configurations to reduce processing time and infrastructure costs while maintaining predictable performance
- Mentor junior and mid level engineers by providing constructive feedback guidance on technical challenges and exposure to modern data engineering practices
Qualifications
- Possess extensive practical experience in PySpark development including writing efficient transformations handling complex joins and managing large scale distributed processing workloads
- Demonstrate strong proficiency in Python programming with focus on modular design error handling logging and integration with cloud native data services for robust pipeline implementations
- Bring hands on expertise with Azure Databricks including workspace configuration job orchestration secret management and integration with broader Azure data platforms such as Data Lake and Synapse
- Apply solid understanding of data warehousing concepts data modeling and ETL ELT patterns to design solutions that support analytics reporting and machine learning use cases
- Utilize knowledge of airline or travel industry data such as reservations operations or customer data as a nice to have capability that enhances domain centric analytics and insights
- Exhibit skill in collaborating within hybrid work models by using modern collaboration tools and clear communication practices to keep distributed stakeholders aligned during day shift operations
- Show capability to troubleshoot production incidents in an organized manner using logs metrics and root cause analysis practices that lead to durable preventive improvements.
Salary and Other Compensation:
The annual salary for this position is between $120-135Kdepending 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。
