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Popular data-engineer title, metro location, and broad platform requirements increase applicant density moderately.
Core data engineering skills transfer across industries, though sector-specific banking/CPG experience increases fit sensitivity.
Requires leadership and specific data platform skills without explicit years, so selection filters are moderately strict.
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Lead and manage a data engineering team to design, build, and implement scalable Big Data solutions and ETL pipelines.
Ensure data quality, integrity, and security while collaborating with stakeholders to meet business requirements.
Provide technical guidance and mentorship while optimizing system performance through data analysis and troubleshooting.
Bachelor's degree in Business Analytics, Computer Science, Statistics, or related; Master's degree in Data Science is acceptable.
Certifications required include Certified Data Management Professional, Databricks Certified Associate Developer for Apache Spark, Microsoft Certified: Azure Data Engineer Associate, or Oracle Database 12c Certified Implementation Specialist.
Proficiency in Agile methodology, Data Engineering skills, and experience with platforms/tools like Databricks and Snowflake.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced leader capable of managing and mentoring a data engineering team in a hybrid work environment.
Strong technical expertise in Big Data technologies, ETL design, cloud platforms (Azure), and data management practices.
Ability to collaborate with diverse stakeholders to translate business needs into scalable and secure data solutions.