Middle-level Data Engineer
2 weeks ago
Location: Bandung/Remote, Indonesia
Benefits: International exposure, WFH incentives
We are looking to hire a skilled data engineer who can create an amazing experience for our customers as they build and maintain solutions and find trends in data sets and develop algorithms to help make raw data more useful to the enterprise.
**Requirements**:
- 3-5 years of professional experience as a Data Engineer, Data Warehouse, Business Intelligence, Data transformation, and/or Data Modelling.
- Design and deploy large-scale data platforms and data warehouses.
- Design and deploy ETL and data ingest tools and strategies in a cloud platform
- Experience with relational systems, object stores, and Google Cloud’s Big Query
- Strong SQL and/or NoSQL database knowledge
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Experience with object-oriented, object function scripting languages such as Python, Java, NodeJS, PHP, etc
- Knowledge of how to use code version control such as Git/SVN
- Able to employ analytical thinking to investigate issues and develop solutions
- Proven ability to collaborate in a multicultural team
- Knowledge of modern education systems and development field is desirable
- Ability to remain focused in a team-oriented environment
- Good verbal and written communication skills (Required language: English)
**Plus**:
- Bachelor’s degree in engineering, computer science, computer engineering, Math, Statistics, Physics.
- Has sufficient working experience in the game industry
- Experience with stream-processing systems in a cloud environment such as AWS or Google Cloud
- Has proficiency and understanding of the platform as a service (PaaS) from the major cloud vendors.
Experience with big data tools such as Hadoop
- Knowledge of visualization tools such as Google Data Studio and Metabase
Strong analytic skills related to working with unstructured datasets**:
- Build and maintain database system and model for the dashboard and report visualization
- Identify, design, and implement internal process improvements to automate manual processes, optimize data delivery, re-designing infrastructure for greater scalability, etc
- Collects, integrates, aggregates, transforms, and wrangles data at scale to enable data science activities, self-service analytics, and production analytics such as machine learning.
- Maintaining our data warehouse and data storage system to make sure it’s reliable and quality.
- Construct code with good coding standards and practices to ensure high quality and minimum risks
- Build analytics tools that utilize the data pipeline to provide actionable insight into customer acquisition, operational efficiency, and other key business performance metrics.
- Work with data and analytics experts to strive for greater functionality in our data systems.
- Keep data separated and secure across national and global boundaries through multiple data centers.
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