Tax Data Engineering Manager – Azure & Databricks Lead

PwC

Washington (District of Columbia)

On-site

USD 99,000 - 266,000

Full time

14 days+

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Benefits offered by this job

Medical insurance
Dental insurance
Vision insurance
401(k) plan
Holiday pay
Vacation
Personal and family sick leave

Job summary

PwC is seeking a Tax Innovation - Data Engineer - Manager to design and build data infrastructure, pipelines, and transformation solutions that enable data-driven decision-making. You will lead teams, mentor staff, and manage client accounts while delivering high-quality data engineering projects.

You will work with Azure Data Factory, Databricks, and Snowflake to implement scalable data architectures and ensure data quality and security.

Qualifications

  • Bachelor’s degree or higher.
  • Minimum 5 years of experience in data engineering or related field.

Responsibilities

  • Designing and implementing data infrastructure and systems for efficient processing and analysis.
  • Developing and managing data pipelines, integration, and transformation solutions.
  • Leading teams in strategic planning and execution of data engineering projects.
  • Utilizing Azure Data Factory and Databricks to enhance data solutions.
  • Building and maintaining data warehouses/lakes for BI and analytics.
  • Overseeing data quality, validation, and security within analytics frameworks.
  • Mentoring team members to develop skills and improve delivery.

Skills

Data engineering
Mentoring/leadership
Analytical thinking

Education

Bachelor’s degree

Tools

Azure Data Factory
Azure Databricks
Snowflake

Job description

PwC is seeking a Tax Innovation - Data Engineer - Manager to design and build data infrastructure, pipelines, and transformation solutions that enable data-driven decision-making. You will lead teams, mentor staff, and manage client accounts while delivering high-quality data engineering projects.

You will work with Azure Data Factory, Databricks, and Snowflake to implement scalable data architectures and ensure data quality and security.

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