Analytics Engineer

5 days ago

Taguig, National Capital Region, Philippines Samsung Southeast Asia & Oceania Full time ₱900,000 - ₱1,200,000 per year

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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