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 an experienced Sr Azure Data Engineer with strong hands-on expertise in PySpark, Azure Synapse Analytics, SQL, Big Data technologies, and modern cloud data engineering practices. The candidate will be responsible for designing, developing, optimizing, and supporting scalable data pipelines, distributed data processing frameworks, and enterprise-grade analytics solutions across Microsoft Azure and Big Data platforms.
Responsibilities :
· Design, develop, and maintain scalable data pipelines using PySpark, Spark SQL, Python, SQL, and Azure Synapse Analytics.
· Build and optimize ETL/ELT workflows for large-volume structured, semi-structured, and unstructured data processing.
· Develop and support Azure Synapse pipelines, notebooks, SQL scripts, stored procedures, views, and data transformation logic.
· Work with Azure Data Lake Storage Gen2, Azure Data Factory, Azure Databricks, Azure SQL Database, and related Azure data services.
· Develop and support Big Data solutions using technologies such as Apache Spark, Hadoop, HDFS, Hive, Sqoop, Kafka, HBase, and related distributed data processing components.
· Translate business requirements and functional specifications into detailed technical designs and reusable data engineering components.
· Implement data ingestion, transformation, validation, reconciliation, and publishing processes across enterprise data platforms.
· Perform performance tuning of PySpark and SQL workloads by optimizing joins, partitioning, caching, file sizing, indexing, and query execution plans.
· Optimize Big Data jobs and distributed workloads by tuning Spark configurations, partitions, memory usage, execution plans, storage formats, and cluster resource utilization.
· Develop reusable frameworks for metadata-driven ingestion, incremental loads, error handling, audit logging, and data quality checks.
· Support unit testing, system testing, UAT, deployment, production monitoring, incident resolution, and post-production support.
· Collaborate with architects, business analysts, QA teams, DevOps teams, platform teams, and client stakeholders to deliver robust data solutions.
· Ensure compliance with data governance, security, lineage, audit, access control, and operational standards.
· Mentor junior data engineers, review code, provide technical guidance, and promote engineering best practices.
Required Skills:
· 8 to 15 years of overall IT experience with a strong focus on data engineering, Big Data platforms, distributed data processing, cloud data solutions, and enterprise data processing.
· Minimum 5+ years of hands-on experience in PySpark, Spark SQL, Python, SQL, and data pipeline development.
· Minimum 4+ years of hands-on experience with Big Data ecosystem tools such as Spark, Hadoop, HDFS, Hive, Kafka, Sqoop, or HBase.
· Minimum 3+ years of practical experience working with Azure Synapse Analytics and Azure cloud data services.
· Proven experience in designing, developing, testing, deploying, and supporting production-grade data engineering solutions.
· Ability to independently own technical design, development, defect resolution, deployment, and production support activities.
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。
