Senior Data Engineer (142264)

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Singtel

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Job Description

Responsibilities:

  • Design, develop and automate large scale, high-performance distributed data processing systems (batch and/or real-time streaming) that meet both functional and non-functional requirements
  • Deliver high level & detailed design to ensure that the solution meet business requirements and align to the data architecture principles and technology stacks
  • Partner with business domain experts, data scientists, and solution designers to identify relevant data-assets, domain data model and data solutions. Collaborate with product data engineers to coordinate backlog feature development of data pipelines patterns and capabilities
  • Own and lead data engineering projects; data pipelines delivery with reliable, efficient, testable, & maintainable artifacts, involves ingest & process data from a large number and variety of data sources
  • Build, optimize and contribute to shared Data Engineering Frameworks and tooling, Data Products & standards to improve the productivity and quality of output for Data Engineers
  • Design and build scalable Data APIs to host Operational data and Data-Lake assert in Data[1]Mesh / Data Fabric Architecture
  • Drive Modern Data Platform operations using Data Ops, ensure data quality, monitoring the data system. Also support Data science MLOps platform 8. Drive and deliver industry standard Devops (CI/CD) best practices, automate development and release management
  • Understand data security standards, use data security guidelines & tools to apply and adhere to the required data controls across data platform, data pipelines, applications and access end points
  • Support and contribute to data engineering product and data pipeline documentations, development guidelines & standards for data-pipeline, data model and layer design

We are committed to a safe and healthy environment for our employees & customers and will require all prospective employees to be fully vaccinated

Requirements:

  • Minimum of 8 years of experience in Data Engineering, Data Lake Infrastructure, Data Warehousing, Data Analytics tools or related, in design and developing of end-to-end scalable data pipelines and data products
  • Experience in building and operating large and robust distributed data lakes (multiple PBs) and deploying high performance with reliable system with monitoring and logging practices
  • Experience in designing and building data products and pipelines using some of the most scalable and resilient open-source big data technologies; Spark, Delta-Lake, Kafka, Flink, Airflow, Presto and related distributed data processing
  • Build and deploy high performance modern data engineering & automation frameworks using programming languages such as Scala/Python and automate the big data workflows such as ingestion, aggregation, ETL processing etc
  • Good understanding of data modeling and high[1]end design, data engineering / software engineering best practices - include handling and logging errors, monitoring the system, fault-tolerant pipelines, data quality and ensuring a deterministic pipeline with DataOps
  • Excellent experience in using ANSI SQL for relational databases like – Postgres, MySql, Oracle and knowledge of Advanced SQL on distributed analytics
  • Experience working in Telco Data Warehouse and / or Data Lake engines – Databricks SQL, Snowflake , etc
  • Proficiency programming languageslike Scala , Python, Java, Go, Rust or scripting languages like Bash
  • Experience on cloud systems like AWS, Azure, or Google Cloud Platform o Cloud data engineering experience in at least one cloud (Azure, AWS, GCP) o Experience with Databrick (Cloud Data Lakehouse)
  • Experience on Hadoop stack: HDFS, Yarn, Hive, HBase, Cloudera, Hortonworks
  • Experience on NoSQL
  • Experience on Event Streaming Platform, Message Queues like Kafka, Pulsar , Rabbit -MQ, Redis -MQ o Event Processing systems – Kafka Streaming, KSQL, Spark Streaming, Apache Flink, Apache Beam etc.
  • Build and deploy using CI/CD toolkits Technical

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