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Metro location and broad, common data engineering skillset yield medium competition density.
Data engineering skills are broadly transferable across industries, with moderate consulting-specific client-fit requirements.
Explicit 7–10 years plus mandatory data engineering and core tech skills makes shortlisting strict.
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Lead and manage execution of data engineering projects independently, focusing on technical solutions for digital marketing, eCommerce, BI, and self-service analytics.
Design and build operational data platforms including ETL pipelines, data lakes, streaming data hubs, and machine learning model support.
Interact with clients at the executive level and guide, mentor, and quality check work of team members within a flat, agile organization.
7-10 years of professional hands-on experience in data engineering and software engineering fields.
Experience managing and leading data engineering and data warehousing projects.
Proficiency in Python, SQL, distributed programming languages (preferably Spark), and knowledge of Unix/Linux systems, containers, and software development practices (Agile).
Work Experience Required: 7-10 years
Experienced leader comfortable interacting with C-level clients and mentoring teams in data engineering projects.
Broad expertise across software engineering disciplines with focus on data processing, distributed systems, and enterprise data warehousing.
Able to operate in agile, flat organizations collaborating closely with strategy consultants and data scientists.