Data Engineer Officer
- Taguig, Philippines32nd Street, Bonifacio Global City, Taguig, Taguig, Metro Manila, PhilippinesTaguigMetro ManilaPhilippines
- Full time
The Data Engineer Officer is responsible for designing and implementing technologies that will support the company’s vision of becoming a data-driven enterprise. He/she 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/she 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 Officer will guarantee compliance with data governance and data security requirements while creating, improving, and operationalizing these integrated and reusable data pipelines. 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.
Key Responsiblities Include:
- Designing, creating, and maintaining efficient and reliable data pipelines from data sources of varying nature (streaming, batch processing etc.) to identified data storage targets.
- Identifying and recommending appropriate data storage technologies for different types of data (event-based, time-series, relational, flat files etc.).
- Working in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
- Using innovative and modern tools, techniques, and architectures to partially or completely automate the most-common, repeatable, and tedious data preparation and integration tasks in order to minimize manual and error-prone processes, and improve productivity.
- Developing best practices for data management, maintenance, reporting, and security.
- Assessing, acquiring, and managing tools and platforms required in the data management lifecycle. Proposing appropriate (and innovative) data ingestion, preparation, integration, and operationalization techniques in optimally addressing these data requirements.
- Ensuring that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives. He/she should work with data governance teams and participate in vetting and promoting content created in the business and by data scientists to the curated data catalog for governed reuse.
- Promoting the available data and analytics capabilities and expertise to business unit leaders and educating them in leveraging these capabilities in achieving their business goals.
- 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 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, 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.
- Any of the following is highly preferred but not required: AWS Certified Solution Architect or Developer, Google Cloud Certified Associate or Professional, any certification equivalent to the aforementioned
Perks and Benefits
- Paid Vacation Leave
- Paid Sick Leave
- Special Leave Benefits for Women
- Child Care Benefits
- Retirement Benefit Plans
- Medical / Health Insurance
- Medical, Prescription, Dental, or Vision Plans
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