BI & Data Engineer (정규직)
- 서울시
- 정규직
- 풀타임
→Design and maintain scalable ETL/ELT pipelines using tools like Databricks (SQL, PySpark), Azure Data Factory, or Apache Airflow
→Build and manage data lake and warehouse structures (e.g., Delta Lake, Unity Catalog, Azure Synapse, Fabric) for structured analytics
→Develop and optimize data models for reporting and automation, following the medallion architecture: raw → silver → gold layers
→Ensure data quality, validation rules, and exception handling across data sources
→ Automate data ingestion from APIs, cloud platforms, ERP/CRM systems, with the underlying security, network setups required in both on-premises and cloud environments
→Integrate DevOps practices: version control (GitHub), CI/CD pipelines, automated testing, and deployment for data flows■ BI / Reporting
→Design and maintain Power BI dashboards, including dataset modeling, dataflows, and paginated reports
→Translate business requirements into KPI frameworks and semantic models
→Optimize Power BI performance (query folding, DAX tuning, aggregations)
→Manage Power BI workspace governance, access control, and deployment pipelines
→Enable self-service BI by creating reusable data models and training business users
→Ensure reporting accuracy and alignment with data from the gold layer or master KPIs■ Cross-Cutting / Shared Responsibilities
→Collaborate closely with business units to define data and insight requirements
→Maintain metadata, documentation, and data lineage transparency
→Support incident handling, refresh monitoring, and data health checks for both data pipelines and dashboards
→Drive data standardization and implement best practices in naming conventions, modeling, and lifecycle management
→Support data democratization and literacy efforts by enabling access to clean, governed data products
→Work closely with the Data Analytics, Engineering, and Automation team members to drive synergy and alignment across projects and initiatives■ Data Governance and Compliance
→Ensure compliance with data governance policies, standards, and regulations
→Establish data quality standards and procedures to maintain data accuracy and reliability
→Implement data governance frameworks to govern data usage, access, and security■ Continuous Improvement
→Stay abreast of emerging trends, technologies, and best practices in data analytics and business architecture
→Identify opportunities for process improvement, automation, and optimization to enhance efficiency and effectiveness
→ Foster a culture of innovation and knowledge sharing within the organization through collaboration and cross-functional teamwork◆Qualifications
■Education
4 year university graduate
Major in computer science, data engineering and analytics, or a related field; advanced degree preferred■Experience
Min 3 years' experience in data analytics, business intelligence and/or science
Additional Experience (2-3 years) in automotive industry, process- and project management or related fields is advantageous■Specific knowledge
→Depth knowledge of data analytics, engineering and science, business architecture, or a related role
→Proficiency in data analysis tools and programming languages such as SQL, DAX, Python, R, etc. as well Microsoft Power Platform automation solutions
→Strong experience with Power BI, including dataset modeling and performance tuning
→Familiarity with Databricks, Delta Lake, Azure Synapse
→Experience with data lake houses, Power Query/M, and structured data modeling
→Knowledge of data governance, KPI definition, and metadata management
→Excellent communication, collaboration, and stakeholder management skills, both Korean and English (verbal, written and presentation)
→Ability to work effectively in a dynamic, fast-paced environment with multiple stakeholders and competing priorities
→Strong problem-solving, adaptability skills and attention to detail[전형절차]
서류전형_면접전형(1차,2차)_최종합격[제출방법/서류]
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