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Strong employer brand, metro location, and a managerial data role create moderate applicant competition.
Data engineering management skills transfer across industries, but required cloud and big-data expertise raise domain specificity.
Mandatory data engineering management experience and specific tech stack (GCP, Spark, SQL, Python) increase selection strictness.
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Lead and develop Data Engineering teams responsible for delivering secure, high-quality, and performant data solutions aligned with product objectives.
Manage delivery execution including timelines, sprint processes, removal of blockers, and ensuring adherence to engineering best practices.
Serve as the primary liaison between Product Managers, Architects, and Engineers to balance technical feasibility with business priorities and ensure alignment on design and standards.
Experience managing Data Engineering teams with skills in SQL, Python, Spark, and Big Data technologies including data warehousing and ingestion.
Required cloud experience, preferably with Google Cloud Platform (GCP).
Proven ability to lead Agile teams, facilitate sprint ceremonies, and oversee technical design reviews and decision-making.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in bridging product priorities with technical execution and managing delivery under pressure in a fast-paced environment.
Demonstrated track record of building accountable, high-performing engineering teams focused on continuous improvement and quality standards.
Strong collaboration skills with clear communication that enable alignment across Product, Architecture, and Engineering stakeholders.