Senior Data & Analytics Engineer

Introduction to Platform Department

The Hyperconnect Infra Department consists of members from Data Engineering, SRE/DevOps/MLOps, Platform, and IT, performing central platform and system infrastructure development and operation roles. We provide infrastructure and common platform technologies to all company services, including Azar and AI/ML, and create business impact in various areas through active collaboration with related departments. We also focus on preventing siloization of the company's technical organizations and creating an efficient and highly productive engineering culture.

Data Product Dev Team

• The Data Product Dev team is an engineering team where Data Engineers gather to perform Data Governance, Analytics Engineering, and BI/DW engineering.
• Beyond simple data pipeline management, we create valuable data and develop and provide sustainable data pipelines and data models where SLO/SLI for Data Quality are managed.
• In DataLake/Warehouse management and development, we adopt Modern Datastack technology paradigms such as Data Governance and Analytics Engineering, and apply Software Engineering practices like version control, testing, deployment, monitoring, and observability to the Data Platform.
• Data (as a) Product: We treat and develop data as a software product. We also act as a bridge between data producers and data consumers, interested in shifting data producers right and data consumers left.
• We create and manage data documentation and metadata to increase the organization's Data Literacy and enhance understanding and utilization of data models.
• Actively contribute to the development of internal and external data products for monetization/statistics/operations based on aggregated data models.

If you join the team

• You can proactively manage data generated in various domain environments based on multi-products.
• Beyond maintaining data pipelines, you can build and design systems to solve business problems based on data.
• If necessary, you can gain experience developing Data Applications required for the business.
• Dealing with global data means the scale is very large (tens of TB/day or more), allowing for various technical considerations and attempts based on large amounts of data.
• You can continuously research better directions and reasonably apply new work systems or system introductions to Production.
• We use EKS, Bigquery, Databricks, Airflow, and you can experience various data infrastructures and frameworks based on public clouds.

Check out how the Data Engineering team works and what problems they solve through our tech blog and Interview X Hacker Ya!

• Interview x Hacker Ya Data Engineering
• BigQuery Storage Optimization Progress

Job Responsibilities

Data Architect (Analytics)

• Implement Data Vault modeling and introduce and build streaming/batch data processing systems based on data modeling.
• Collect needs from various stakeholders to define company-wide data standards.
• Develop end-to-end data analysis architecture including data integration, data warehousing, data modeling, data visualization, and reporting.
• Design and optimize data models to support efficient data storage, retrieval, and analysis, ensuring data integrity, accuracy, and reliability.
• Act as a bridge between business and data to improve the data environment for optimal decision-making.
• Transform complex data into understandable insights and actively achieve new business opportunities.

Data Quality Management

• Automate verification of data consistency, timeliness, and errors.
• Create and operate a single data source for data quality operational management.

BI Operation, Design, and Implementation

• Collaborate with various company-wide organizations to establish policies for BI operations.
• Analyze data user/analyst requirements to design and implement dashboards.

Data Analysis Engineering

• Collaborate with data science/analysts to perform BI and analytics engineering tasks to enable fast EDA and data analysis.
• Build and expand integrated data modeling for data democratization.
• Produce and manage Hyper Data (Data Catalog and Data Knowledge).
• Establish and guide policies to activate data user self-service.

Data Application Development

• Produce streaming tables that can be used in business and backend/ML.
• Beyond analysis, develop Data Applications using Datalake-based data to improve monetization, operations, and engagement efficiency.
• Develop Data Applications for Privacy and Security related data processing and provision.
• Generate and provide near real-time data dashboards and aggregated data.
• Utilize and develop ReverseETL tools based on the produced data mart models to link data with various third-party systems.

Requirements

• Professional data work experience of 6 years or more, with at least 3 years of Data Analytics Engineering experience.
• Able to concisely and systematically implement what you want to analyze using SQL.
• Proficient in basic CS knowledge and Python.
• Proficient in Tableau, Power BI, Looker or similar BI tools.
• Familiar with leading data governance standards and integrated operations across organizations and managing data quality.
• Strong problem-solving skills and ability to design scalable and efficient data analysis architectures.
• Experience leading DW/DM data modeling, pipeline construction and operation.
• Quickly grasp business and various domain scopes, and proactively solve data problems.
• Proficient in Airflow (ETL) and able to collaborate and lead troubleshooting with various stakeholders.
• Able to communicate in basic everyday English.
• Experience using public cloud platforms such as AWS, Google Cloud in practice.

Preferred Qualifications

• Experience building data governance and data platforms with excellent results.
• Experience leading and optimizing effective BI governance across large-scale data and various organizations.
• Experience achieving results using tools like dbt to improve data quality management and pipeline efficiency.
• Enjoy quickly understanding new business domain knowledge and contributing to data-driven decision-making.

How We Work

• Define undefined tasks and find solutions independently.
• Successfully lead team projects, drive inter-team collaboration, and work with partners from other functional roles.
• Communicate clearly and concisely, tailoring messages to the audience both within and outside the team.
• Support inter-team collaboration and help achieve results.
• Align project outcomes with team goals.

Employment Type/Recruitment Process/Working Hours

• Employment Type: Full-time
• Recruitment Process: Document Screening > Technical Competency Test > Recruiter Call > 1st Interview > 2nd Interview > 3rd Interview (if applicable) > Final Offer (* Additional interview stages may be conducted if necessary.)
• For document screening, only successful candidates will be notified individually.
• Application Documents: Free-form detailed resume based on career (Korean or English, PDF)
• This position is available for military service exemption (specialized research personnel) for active duty/transfer and supplementary service/transfer. For military service exemption personnel, service management will be conducted according to relevant military service laws.

If any false information is found in the submitted content or if there are disqualifying reasons for employment under relevant laws, employment may be canceled. If necessary, additional screening and document verification may be conducted beyond the recruitment process notified in advance.

National meritorious persons are given preferential treatment according to relevant laws; if applicable, please notify us when applying and submit supporting documents upon employment.

When applying for a position at Hyperconnect, this privacy policy applies to the processing of personal information: https://career.hyperconnect.com/privacy