Data Engineering Officer  

The Data Engineer is responsible for designing and implementing technologies that will support the company’s vision of becoming a data-driven enterprise. He will serve as the subject matter expert in crafting the platform to support data extraction, storage, processing and consumption requirements of the business. Together with the rest of the Data Platforms team, he will help create strategies, guidelines/policies, best practices and technology assessment criteria for the whole data management lifecycle including intake, integration and enrichment, discovery and consumption, and governance.

The Data Engineer will guarantee compliance with data governance and data security requirements while creating, improving and operationalizing these integrated and reusable data pipelines. This would enable faster data access, integrated data reuse and vastly improved time-to-solution for Aboitiz data and analytics initiatives. The data engineer will be measured on their ability to integrate analytics and (or) data science results with Aboitiz business processes. This role will require both creative and collaborative working with IT and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of data and analytics. The data engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions.

Required Experience:

Bachelor of Science Degree in Computer Science, Information Technology, Engineering, Statistics, Mathematics or any related field An advanced degree in computer science (MS), statistics, applied mathematics, information science, data management, information systems, information science (postgraduate or related) or a related quantitative field is preferred.

At least 6 years or more of work experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks. At least 3 years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative. Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata, and workload management. The ability to work with both IT and business in integrating analytics and data science output into business processes and workflows. Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flows and helping to move them in production. Strong experience in working with both open-source and commercial message queuing technologies such as Kafka, JMS, Azure Service Bus, Amazon Simple Queuing Service, others, stream data integration technologies such as Apache Nifi, Apache Beam, Apache Kafka Streams, Amazon Kinesis, others and stream analytics technologies such as Apache Kafka KSQL Apache Spark Streaming Apache Samza, others.

Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms. Demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service and others. Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization. Deep conglomerate knowledge or previous experience working in the business would be a plus. Strong experience supporting and working with cross-functional teams in a dynamic business environment. Required to be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. The successful candidate will also be required to have regular discussions with data consumers on optimally refining the data pipelines developed in nonproduction environments and deploying them in production. Required to have the accessibility and ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company. Is a confident, energetic self-starter, with strong interpersonal skills. Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

Competencies:

• Business Anaysis
• Interpersonal Skills
• Hardware and Networking Technologies
• Software Design and Architecture
• Information / Operational Technologies
• Advanced Skills in the following technologies:
  • Big data tools: Spark, Hive, Hadoop
  • Relational databases: Postgre, MySQL, MSSQL, x
  • NoSQL databases: Cassandra, MongoDB, CouchDB
  • Cloud Services: AWS, Azure, GCP
  • Data Pipeline tools: Apache Oozie, Airflow, Talend, Attunity, Kafka
  • Data Visualization: Tableau, PowerBI, GoogleDatastudio
  • Programming Languages: Python, R, Java, C++, Scala, and/or other object-oriented programming languages
  • Operating Systems: Unix based OS, MS Windows
• Reaserch and Development
• Inter-Personal and Presentation Skills