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PRICE WATERHOUSE COOPERS

Data Engineer - Manager

PRICE WATERHOUSE COOPERS
Stamford, CT $99k - $232k/yr Full time Posted 7d ago
Manager Analytics Cloud Operations Data Analysis Data Analytics Data Architecture Data Engineer Data Integration Data Pipeline Data Platform Data Processing Data Warehouse Database Databricks ETL SQL
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Job Description

PwC offers a hybrid, Stamford, CT based Data Engineer - Manager role that emphasizes leadership, client impact, and hands-on data engineering. You will design and deploy data infrastructure to enable efficient processing and analytics, lead project teams, and steer client accounts toward data-driven growth. The role comes with a competitive salary ranged from USD 99,000 to 232,000 per year and a comprehensive benefits package that includes medical, dental, vision, 401k, holiday pay, vacation, and personal and family sick leave.

Benefits

  • Medical
  • Dental
  • Vision
  • 401k
  • Holiday pay
  • Vacation
  • Personal and family sick leave

Responsibilities

  • Architect and deploy data infrastructure and systems that enable efficient processing and analytics
  • Build and manage data pipelines, integrations, and transformation processes that meet client requirements
  • Leverage AWS and Azure Data Factory to strengthen data engineering capabilities
  • Lead teams through strategic planning and execution of data driven projects
  • Oversee scalable solutions built on Databricks and Snowflake
  • Mentor team members in data architecture design and database optimization
  • Ensure data quality, security, and compliance within analytics frameworks
  • Identify opportunities to leverage data for growth and performance gains
  • Mentor junior staff to develop skills and promote innovation
  • Address conflicts and engage in strategic discussions with clients and stakeholders

Requirements

  • Bachelor's degree required
  • 4+ years of relevant experience

Technologies

  • Amazon Web Services (AWS)
  • Azure Data Factory
  • Databricks
  • Snowflake

What sets you apart

  • Preferred study areas include Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics
  • Hands-on experience with AWS and Azure Data Factory for data engineering
  • Experience shaping data architecture and optimization strategies with Snowflake and Databricks
  • Experience implementing data anonymization and security best practices in complex systems
  • Strength in dimensional modeling and managing data pipelines
  • Proven ability to lead teams in data warehouse troubleshooting and performance tuning
  • Experience mentoring junior staff in data strategy and validation techniques

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