Role Overview

PCCW Global is looking to expand the Technology Department with a Senior Data Engineer responsible for designing and delivering data pipelines (both streaming and batch) composed of state of the art big data processing systems, while also leading statistical and forecasting analysis efforts or willingness to delve into the ML field within an interdisciplinary Agile team.

Key Responsibilities

• Design, implement and maintain data processing pipelines using state of the art data processing frameworks or in-house developed components. This includes ingestion, transformation, aggregation and storage of both streaming and batch data.
• Manage and correlate data from various sources (both SQL and NoSQL).
• Take ownership of the software development process for both customer-facing and internal BI-extraction tools.
• Work as a key member of an Agile Team.
• Spearhead statistical and forecasting analysis.
• Able to appropriately convey results to both technical and non-technical colleagues.
• Extract valuable insights and discover interesting patterns in data.
• Ensure quality and proper curation of the data. 

Minimum Qualifications

• Bachelor's Degree in Computer Science, Data Science, Mathematics, or other related technical fields involving quantitative analysis.
• 1+ years of experience in a Data Engineering position
• Experienced in at least one of Python, Java/Scala languages and scripting.
• Experience with distributed data processing systems e.g. Spark, Flink.
• Solid understanding of SQL (e.g. Postgres, MySQL) and No-SQL (e.g. Elasticsearch, Redis) database systems.
• Experience creating and using machine learning algorithms and solid background in Statistics.
• Superb communication and presentation skills, team player.
• Analytical mind and business acumen.
• Self-motivated, fast learner and dependable.

Preferred Qualifications

• 4+ years of proven track record in Data Engineering.
• Experience with streaming sources e.g. Kafka, Pub/Sub.
• Familiarity with scheduling/orchestration systems (e.g. Airflow).
• Experience with Jupyter or BI tools (e.g. Looker, Tableau).
• Experience with various kinds of NoSQL databases (KV, Document, Columnar).
• Experience with Cloud Platforms: Google Cloud, Amazon Web Services, Microsoft Azure, – certifications considered a plus.
• Experience with Elasticsearch and its ecosystem.