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Job Description

Data Engineer - Manager role in Stamford, CT (hybrid) with a salary range of USD 99,000 - 232,000 per year.

Responsibilities

  • Design, build, and deploy data architectures and platforms that enable efficient data processing and analytics.
  • Create and manage data pipelines, integrations, and transformations to meet client requirements.
  • Leverage AWS and Azure Data Factory to optimize data workflows and engineering capabilities.
  • Lead teams through strategic planning and delivery of data driven initiatives.
  • Oversee the deployment of scalable data solutions on Databricks and Snowflake.
  • Mentor team members in data architecture design and database performance optimization.
  • Ensure data quality, security, and compliance within analytics frameworks.
  • Identify opportunities to leverage data for growth and performance improvements.
  • Provide mentorship to junior staff to develop skills and foster innovation.
  • Address conflicts and engage in critical conversations with clients and stakeholders.

Requirements

  • Bachelor's degree required.
  • Minimum 4 years of experience.

Technologies

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

Benefits

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

What Sets You Apart

  • Preferred educational backgrounds include MIS, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics.
  • Experience using AWS and Azure Data Factory for data engineering tasks.
  • Ability to design data architecture and optimization strategies with Snowflake and Databricks.
  • Implementing data anonymization and security best practices in complex systems.
  • Strength in dimensional modeling and data pipeline management.
  • Leadership in data warehouse troubleshooting and performance tuning.
  • Mentoring junior staff in data strategy and validation techniques.

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