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Tier-1 brand, mid-level generalist data role, and likely metro hiring increase applicant competition.
Core data engineering and BI skills transfer across industries, though enterprise governance adds moderate specialization.
Explicit 4–6 years plus required SQL, Python, BigQuery, and Power BI increase screening strictness.
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Develop and maintain scalable data pipelines, ETL/ELT processes, and enterprise reporting solutions using cloud data platforms like Google BigQuery.
Create complex SQL queries, data transformations, and Power BI dashboards to support data governance, quality, and analytics initiatives.
Collaborate with business, technology, and risk teams to translate requirements into data products that enhance data control and self-service reporting capabilities.
4-6 years of experience in data engineering, analytics, business intelligence, or related fields.
Strong proficiency in SQL and hands-on experience with Python for data engineering and automation.
Experience with cloud data warehouse technologies such as Google BigQuery and developing Power BI or Tableau dashboards.
Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Analytics, Engineering, or related field.
Experienced in building scalable cloud-native data pipelines and enterprise data platforms with a focus on data governance and data quality.
Proficient in translating complex business requirements into reusable data products and self-service analytics solutions.
Familiar with Agile cross-functional team environments and working with stakeholders across business, technology, and risk management.