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Common data-engineer lead with broad AWS/PySpark requirements in a metro market increases applicant competition.
Core data engineering skills (PySpark, AWS, SQL) transfer easily across industries.
Mandatory AWS, PySpark, SQL, ETL, and support leadership imply strict technical and delivery filters.
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Manage end-to-end customer engagement and service delivery for cloud data warehouse support within a fast-growing software environment.
Lead application support operations including incident triaging, resolution, monitoring, SLA compliance, and stakeholder communication.
Drive process improvements, mentor offshore teams, and oversee defect management and incident resolution in collaboration with third-party vendors.
Experience in application support and incident management within cloud data warehouse or similar environments: Not explicitly quantified.
Proficient in Python, PySpark, SQL, ETL tools, AWS services (Glue, Athena, Lambda), and DevOps practices including infrastructure as code and CI/CD.
Graduation in Computer Science, Data Science, or related field required.
Experience with performance tuning, data warehouse architecture, and development on single (SQL Server, Oracle) and parallel platforms (AWS Redshift).
Experienced in managing client engagements and customer service operations with strong communication and leadership skills.
Technical expertise in data warehouse technologies combined with operational ownership of SLA-driven support teams.
Capable of working in Agile methodologies and mentoring offshore teams on delivery and process adherence.