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Tier-1 brand, mid-level generalist data engineer role in a metro drives high applicant competition.
Core data engineering skills are transferable, though Salesforce/Customer Success BI knowledge adds moderate domain specificity.
Explicit 6–8 years plus mandatory Python, Airflow, and Snowflake/Oracle requirements increase shortlisting rigor.
Develop, implement, and maintain data pipelines to move and process data efficiently into BI schemas for Tableau dashboarding.
Collaborate with cross-functional teams to gather, process, analyze, and present business intelligence data for customer success metrics and stakeholder needs.
Mentor junior data engineers, enforce data governance best practices, monitor daily data processes, and resolve data issues to ensure accuracy and compliance.
6-8 years of experience in a data engineering role supporting business intelligence teams.
Proficiency in Python, Airflow, and databases such as Oracle and Snowflake, including writing complex SQL queries.
Bachelor's or Master's degree in Computer Science or equivalent.
Work Experience Required: At least 6-8 years in data engineering; Notice Period: Not explicitly mentioned in the JD.
Experienced in end-to-end BI data engineering with a focus on building and optimizing data pipelines and dashboards tailored to business stakeholders.
Strong technical leadership demonstrated through mentoring junior engineers and overseeing data governance and quality in a large-scale enterprise environment.
Familiar with integrating data from sources like Salesforce Org and knowledgeable about AI applications to enhance productivity and automation workflows.