Sr. Data Engineer (Data Platform)

Key Skills

Analytical and Problem solving, ETL frameworks, GoLang, JavaScript, matplotlib, Natural Language Processing (NLP), NumPy, Pandas, Python Programming, PyTorch, RNNs, Scala Programming, Scikit-learn

Job Description

About us

Gogolook is a leading TrustTech company established in 2012. With Build for Trust as its core value, it aims to create an AI- and data-driven global anti-fraud network as well as Risk Management as a Service. From multi-communication to fintech and SaaS, Gogolook creates trustworthy empowerment with the use of technology in various fields.

Gogolook has also teamed up with a number of institutes such as the Taiwan National Police Agency Criminal Investigation Bureau, the Financial Supervisory Service of South Korea, Thai Police Cyber Taskforce and the Fukuoka city government to fight fraud and ultimately, to build a trustworthy communication network across the world.

Why you should join Gogolook

• Influential products: What we make are meaningful products that create values for society and defend against frauds.
• Emphasize self-growth: We encourage technical community activities, subsidize tickets for conferences and workshops so that learning is continuously supported by the company.
• Unleash your talent: We respect the professional opinions of everyone, encourage team members to discuss with each other, and make awesome products together.
• Transparent culture: We publicly share the company's information to all, every member can read and feedback, and become a part of participating in the proposal.

As a Data Platform Engineer in Gogolook, you will play a critical role in designing, building, and maintaining our data platform infrastructure. You will collaborate with cross-functional teams to ensure data availability, reliability, and scalability for our organization's growing data needs. If you are passionate and looking to implement DataOps practices fostering collaboration and automation in data workflows, we invite you to join our team as a Data Platform Engineer.

Responsibilities

• Design and construct comprehensive ETL pipelines for high-performance, large-volume applications.
• Build and enhance the data architecture to support business intelligence systems and product applications.
• Implement data governance and security measures to ensure data privacy and compliance with relevant regulations.
• Create automation processing to reduce development time and increase data reliability.

Minimum qualifications

• Minimum of 3 years of hands-on software development experience in languages such as Python, Scala, Java, Golang, etc.
• With expertise in optimizing data flow and processing efficiency and experience handling data throughput of up to 1 million records per hour.
• Hands-on experience with cloud platforms like AWS, GCP or Azure.
• Proficiency in developing robust data pipelines, including data collection and ETL(Extract, Transform, Load) processes.
• Experience designing and implementing various components of a data platform, including data ingestion, storage, data warehousing, data orchestration.
• Experience deploying infrastructure as code using CloudFormation or Terraform in AWS, GCP or Azure.
• Experience in continuous integration and continuous deployment(CI/CD) processes.

Preferred qualifications

• Experience in Docker, Kubernetes or Helm Charts.
• Experience in machine learning platforms, like KubeFlow, MLflow or Vertex AI.
• Has experience with API design and implementation.
• Has experience using streaming tools like Kafka, AWS Kinesis, Spark streaming or Flink.