
Data Engineer
4 weeks ago
Responsibilities
- Develop, test, monitor and optimize end-to-end data processing jobs and workflows from data acquisition, transformation to data exposure/publishing.
- Develop and enhance applications/solutions/software consuming data from the data lake/data warehouse for data visualization or advanced data analytics (i.e., reports and dashboards).
- Develop, test and maintain big data architecture and open-source databases (e.g., Hadoop, Hive, HBase, Presto), including duties to support development and deployment of innovative big data platforms.
- Establish controls on data collection, processing and transformation; perform regular data quality audits (accuracy, completeness and timeliness) and ensure compliance to PLDT Group standards.
- Collaborate with business users, data owners and stewards, IT hardware support and infrastructure teams, IT data source teams, database administrators and other stakeholders to clarify requirements, communicate status, issues or present solutions.
- Manage day-to-day running of scheduled jobs or programs, enforce policies, maintain systems, respond to user requests and ensure that the system delivers consistently on the operational-level agreement (OLA). In case of issues, be responsible for prompt resolution related to end-to-end data platform components.
- Ensure delivery commitments of 3rd party vendor partners within service-level agreements (SLA) for troubleshooting, applying patches, handling exceptions and escalating problems.
- Perform other related duties of similar nature as assigned; support upgrades or migrations to keep technology up to date.
- Diagnose issues and synthesize conclusions into recommendations that drive improvements to the overall delivery.
- Create Solutions Design and Technical Architecture documentation.
- Graduate of any bachelor’s degree in Computer Science, Information Systems/Technology, Engineering or related field (or equivalent project-related experience).
- Working knowledge in Python, Perl, C/C++, PL/SQL, NoSQL and Java
- Linux and Unix is required
- Knowledge and experience in Big Data technologies like HDFS, Hadoop, Apache Spark is a plus
- End-to-End software development lifecycle
- Associate
- Full-time
- Information Technology
- Telecommunications
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