Job Description

Collaborate with stakeholders (customers, partners, colleagues) on data-related technical issues and infrastructure needs. Work with data scientists to gather data requirements for modeling. Design, develop, document, manage, and maintain data models, ETL processes, data warehouses, data management, and pipeline solutions for large volumes of structured/unstructured data from various sources with different latencies (on-demand, batch, real-time, near-real-time). Define, monitor, and report SLAs for data pipelines and products. Execute data quality assurance practices. Support data management solutions pre-sales initiatives, proposal development, and provide post-sales support.

Technical Knowledge/Skills/Competencies

Expertise in relational/non-relational/NoSQL databases and enterprise data warehouses/marts. Proficiency in big data technologies (e.g., Hadoop, Spark, Hive, HBase). Knowledge of data ingestion technologies (e.g., Flume, Kafka, NiFi). Experience in scripting, programming, and software development (e.g., Java, C/C++, Python, R, MATLAB, Scala, SQL) for Windows or Linux. Experience in master data management, data governance, and data lifecycle management. Skilled in designing, documenting, implementing, and supporting data management solutions. Familiarity with software engineering best practices (development, programming, testing, version control). Knowledge of data privacy and security assurance. Understanding of machine learning, computer vision, and large language models is a plus.



(EA Reg No: 20C0312)


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