Analytics Engineer
5 days ago
Disclaimer: Samsung has a strict policy on trade secrets. In applying to Samsung and progressing through the recruitment process, you must not disclose any trade secrets of your current or previous employer.
Responsibilities:
Data Pipeline Optimization and Development
- Designs and develops data requirements for upcoming features by collaborating closely with application teams and business teams from North America and South Korea
- Builds robust ETL/ELT pipelines in Python to support business needs, while ensuring scalability and performance.
- Designs and develops and automates the generation of data marts aligned with business needs
Implement data governance best practices to ensure data quality
- Spearheads testing sessions and exercises with teams to assess data quality, accuracy, metric alignment, and consistency across various systems and reports.
- Leads the development and maintenance of technical documents regarding the datasets within the team to ensure long-term sustainability of operations.
- Ensures accuracy and reliability of dashboards for executives, business teams, product teams, and operations teams.
- Proactively shares and implements best practices and new developments regarding data governance and improvement of data quality.
Analytics Support and Collaboration
- Provides assistance with day-to-day data requirements if needed (eg. custom data requests)
- Work closely with data scientists, data analysts and data engineers to improve processes, operations, ways of working, and develop future projects and initiatives
- Develops and creates dashboards and reports if needed
Qualifications:
- Relevant previous work experience (Business Intelligence, Enterprise Data Management, Data Governance, Data Engineering), reports / dashboard creation.
- Mandatory: Skilled in SQL.
- Experience using Tableau, OR Experienced with SAS / Power BI / Looker Studio and willing to learn Tableau.
- Experience working in mobile payments, e-commerce, fintech, or any industry with complex data ecosystems (eg. multiple data sources, high data volume, high velocity data processing requirements) is highly advantageous.
- Bachelor degree in Computer Science, Mathematics or Statistics preferred but not required.
- Experience using cloud-based Data Warehouses (BigQuery, Redshift) is a plus.
- Candidates with experience in coding Data Pipelines in Python, Spark, and/or Airflow are preferred.
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