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Tier-1 brand, common data-engineer title, metro location and broad platform requirements increase applicant competition.
Core data engineering skills are transferable, but required cloud/warehouse platform experience limits portability somewhat.
Explicit seniority plus many mandatory platforms and leadership expectations make filtering strict.
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Design, build, and optimize scalable data pipelines and platforms to support analytics, reporting, and downstream applications using technologies like Snowflake and Databricks.
Ensure data quality, governance, and lineage across diverse storage solutions including cloud platforms and distributed processing frameworks.
Lead cross-team initiatives, mentor junior engineers, and contribute to development of internal data engineering tools and best practices.
8-10+ years of experience in Data Engineering or related roles.
Proficiency in advanced SQL and Python (or similar programming language).
Experience with distributed computing frameworks (e.g., Apache Spark), Snowflake, Databricks, and cloud data warehouse management (AWS, GCP, or Azure).
Bachelor's Degree preferred; combinations of coursework and related experience may be considered.
Experienced in leading complex, high-impact data engineering projects and driving architectural best practices.
Strong background in large-scale data system design with expertise in data quality, validation, transformation, and lineage.
Capable of collaborating across teams to improve data sourcing and processing efficiency and mentoring junior engineers.