Good understanding of data engineering concepts, data transformation techniques, and tools such as Fivetran, DBT, Snowflake, and QuickSight or Tableau.
Proficient in Python, including libraries such as Pandas, for data cleaning and transformation.
Experience building and maintaining data pipelines from common data sources.
Understanding of data modelling methodologies and normalization principles for data warehousing.
Experience implementing data quality checks and following data governance practices.
Familiarity with data visualization tools and best practices for effective dashboards.
Strong SQL skills for querying and transforming data.
Good communication skills, able to collaborate with stakeholders on data requirements.
Academic and professional requirements
Bachelor's degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience.
2–4 years of experience in data engineering or a related role.
Nice-to-have skills (preferred)
Experience with Snowflake performance optimization.
Exposure to workflow orchestration tools.
Familiarity with data governance frameworks.
GK
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