Cognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process services, dedicated to helping the world's leading companies build stronger businesses. Headquartered in Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry and business process expertise, and a global, collaborative workforce that embodies the future of work. Cognizant is a member of the NASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing and fastest growing companies in the world.
Our Culture:
Your passion, integrity and experience are integral to Cognizant's success. You will join a dynamic and expanding global leader in IT and Business consultancy where you will be valued for who you are. We take pride in our partnership with our clients, so your ability to add value and provide exceptional service to our clients is fundamental to your success. In return, you will be presented with opportunities to develop your career and collaborate with talented colleagues in a supportive, diverse environment.
At Cognizant we recognize that companies that are open and welcoming to a multi-culturally diverse workforce will thrive with fresh perspectives and collaborative knowledge. Cognizant focuses on promoting & increasing gender diversity and providing a workplace which encourages great participation and an equal playing field, where merit and accomplishment are the only criteria for success.
Job Summary:
We are looking for a technically strong Senior Data Engineer with 8 to 15 years of experience in designing, developing, and supporting enterprise-scale data engineering solutions. The role requires a strong combination of PySpark, Azure Synapse, Informatica PowerCenter, Informatica Intelligent Cloud Services (IICS), and SQL skills. The candidate must have hands-on experience in building scalable data pipelines, integrating data across cloud and on-premise platforms, and delivering reliable, performance-optimized data solutions.
Responsibilities:
- Design, develop, and maintain scalable data pipelines using PySpark, SQL, Azure Synapse, Informatica PowerCenter, and IICS.
- Build batch and near-real-time data integration solutions for structured, semi-structured, and large-volume datasets.
- Develop and optimize Spark-based transformations using PySpark, Spark SQL, DataFrames, partitioning, caching, and performance tuning techniques.
- Work on Azure Synapse Analytics for data warehousing, pipeline orchestration, transformation logic, and analytics-ready data processing.
- Design, develop, and maintain Informatica PowerCenter mappings, sessions, workflows, reusable transformations, parameter files, and deployment objects.
- Develop and support IICS assets including mappings, mapping tasks, taskflows, connections, schedules, and cloud data integration processes.
- Write complex SQL queries, stored procedures, views, and performance-optimized data transformation logic across relational databases and cloud data platforms.
- Perform data analysis, data profiling, validation, reconciliation, and data quality checks to ensure accuracy and completeness of data pipelines.
- Troubleshoot production issues, identify root causes, optimize jobs, and ensure timely resolution of data processing failures.
- Collaborate with architects, business analysts, source system teams, QA teams, and downstream consumers to understand requirements and deliver robust solutions.
- Follow engineering best practices including version control, code reviews, reusable components, documentation, CI/CD, and environment promotion processes.
- Mentor junior data engineers and provide technical guidance on design, development, optimization, and issue resolution.
Required Skills:
- PySpark: Strong hands-on experience in developing distributed data processing pipelines, transformations, Spark SQL logic, and performance-tuned Spark jobs.
- Azure Synapse: Hands-on experience with Synapse Pipelines, Synapse SQL, Spark Pools, notebooks, linked services, and integration with Azure data storage.
- Informatica PowerCenter: Strong development experience in mappings, sessions, workflows, transformations, parameterization, scheduling, troubleshooting, and performance tuning.
- IICS: Hands-on experience in Informatica Cloud Data Integration, mappings, mapping tasks, taskflows, connectors, schedules, monitoring, and error handling.
- SQL: Advanced SQL skills including complex joins, analytical functions, query optimization, stored procedures, views, data validation, and reconciliation.
- Data Engineering: Strong understanding of ETL/ELT design, data warehousing, data lake concepts, data modeling, ingestion patterns, and pipeline orchestration.
- Production Support: Ability to debug failures, analyze logs, resolve data issues, tune jobs, and support critical production data pipelines.
Benefits:
Joining Cognizant will give you the opportunity to learn and collaborate with some of the most talented people in the industry, while having your finger on the pulse of emerging industry trends and working on the cutting edge of technology in your field of expertise.
We recognize that our people perform at their best when they feel valued as significant contributors and that is why at Cognizant, taking care of our employees is a priority:
· You can pursue innovative career tracks and opportunities here
· You can enhance your professional development through education and dedicated training
· We’ll give you the skills you need to keep pace with the changing workplace while our compensation, benefits and wellness packages help you stay healthy and plan for the future.
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。
