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PwC brand, metro location, mid-level data role with broad cloud and ETL skills creates high competition.
Airflow, Snowflake and Databricks skills are technology-focused and highly transferable across industries.
Explicit 4+ years requirement plus specific ETL and cloud tooling increases shortlisting strictness to medium.
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Design, develop, and maintain ETL processes and automated data pipelines using Apache Airflow and DAGs to support data integration and transformation.
Implement and optimize scalable data solutions leveraging AWS, Azure Databricks, Snowflake, and other data warehousing technologies.
Collaborate with cross-functional teams to build data lakes and warehouses, ensuring data quality and system performance through validation and administration.
Bachelor's degree in any field.
Minimum 4 years of relevant ETL or data engineering experience.
Proficiency in English (oral and written).
Experience with Apache Airflow, AWS or Azure, and data warehousing platforms such as Snowflake or Databricks is implied but not explicitly mandated.
Background in Management Information Systems, Computer Science, Engineering, Mathematics, or Statistics fields is preferred.
Experience managing complex data pipelines and data architecture in cloud environments using Airflow, Snowflake, Databricks, and Azure Data Factory.
Ability to analyze complex data engineering challenges, optimize database performance, and implement data anonymization techniques.