Data Engineer

3 weeks ago


Singapore Cognizant Full time
Job Title: Data Engineer

We are seeking a highly skilled Data Engineer to join our team at Cognizant. As a Data Engineer, you will be responsible for designing, developing, and deploying large-scale data pipelines and architectures.

Key Responsibilities:
  • Data Pipeline Development: Design, build, and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.
  • Data Integration: Integrate and collate data silos in a scalable and compliant manner.
  • Collaboration: Collaborate with cross-functional teams, including Project Managers, Data Architects, Business Analysts, and Frontend Developers, to build scalable data-driven products.
  • API Development: Develop backend APIs and work on databases to support applications.
  • Agile Environment: Work in an Agile Environment that practices Continuous Integration and Delivery.
Requirements:
  • Proficiency in Data Cleaning and Transformation: Proficient in general data cleaning and transformation (e.g., SQL, pandas, R, etc.).
  • ETL Pipeline Development: Proficient in building ETL pipeline (e.g., SQL Server Integration Services (SSIS), AWS Database Migration Services (DMS), Python, AWS Lambda, ECS Container task, Eventbridge, AWS Glue, Spring).
  • Database Design and Experience: Proficient in database design and various databases (e.g., SQL, PostgreSQL, AWS S3, Athena, MongoDB, Postgres/gis, MYSQL, SQLite, voltdb, Cassandra, etc.).
  • Cloud Experience: Experience in cloud technologies such as GPC, GCC (i.e., AWS, Azure, Google Cloud).
  • Big Data Environment: Experience and passion for data engineering in a big data environment using Cloud platforms such as GPC, GCC (i.e., AWS, Azure, Google Cloud).
  • Production-Grade Data Pipelines: Experience with building production-grade data pipelines, ETL/ELT data integration.
  • System Design and Data Structure: Knowledge about system design, data structure, and algorithms.
  • Data Modelling and Storage Infrastructure: Familiar with data modelling, data access, and data storage infrastructure like Data Mart, Data Lake, Data Virtualization, and Data Warehouse.
  • API and Web Requests: Familiar with rest API and web requests/protocols in general.
  • Big Data Frameworks and Tools: Familiar with big data frameworks and tools (e.g., Hadoop, Spark, Kafka, RabbitMQ).
  • Web Scraping: Familiar with W3C Document Object Model and customized web scraping (e.g., BeautifulSoup, CasperJS, PhantomJS, Selenium, Nodejs, etc.).
  • Scripting Language: Comfortable in at least one scripting language (e.g., SQL, Python).

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