Job description

Data Engineer - Manager

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Job Category:   Analytics|Information Technology
Line of Service:   Assurance
Location(s):   FL-Tampa
Travel Requirements:   0-20%
Level:   Manager
Job ID:   103794BR
PwC/LOS Overview
PwC is a network of firms committed to delivering quality in assurance, tax and advisory services.

We help resolve complex issues for our clients and identify opportunities. Learn more about us at

At PwC, we develop leaders at all levels. The distinctive leadership framework we call the PwC Professional ( provides our people with a road map to grow their skills and build their careers. Our approach to ongoing development shapes employees into leaders, no matter the role or job title.

Are you ready to build a career in a rapidly changing world? Developing as a PwC Professional means that you will be ready
- to create and capture opportunities to advance your career and fulfill your potential. To learn more, visit us at

What will you do if you work in Assurance at PwC?
You'll ask questions and test assumptions. You'll help determine if companies are reporting information that investors and others can rely on. You'll help businesses solve complex issues faced by management and boards. You'll serve the public interest and the capital markets by conducting quality audits. Visit for more information on PwC's Assurance practice.

The world is quickly changing, that's why PwC is quickly adapting. We're capitalizing on trends that will impact corporate reporting.

Our focus is on globalization, technology, sustainability and environmental reporting, population shifts and regulation. We combine skills and experience to help our clients address their challenges.

Job Description
The Assurance Innovation group is developing capabilities leveraging the latest in Open Source technologies to automate and accelerate our client engagements across the enterprise. We are focused on incorporating the latest in machine learning, Big Data, NoSQL, cutting edge development languages,

and advanced data processing techniques to include structured and unstructured information in a loosely coupled ecosystem delivering a technology platform that positions PwC for the future.

As a Data Engineer, you will work in a team together with Data Scientists, Software Engineers and Product Managers to drive Innovation and Technical solutions into the practice.

Data Engineers will focus on the design and build out of data models, codification of business rules, mapping of data sources to the data models (structured and unstructured), engineering of scalable ETL pipelines, development of data quality solutions, and continuous evaluation of technologies to continue to enhance the capabilities of the Data Engineer team and broader Innovation group.

Position/Program Requirements
Minimum Year(s) of Experience: 5

Minimum Degree Required: Bachelor's degree or 8 years in the design and build-out of data models, codification of business rules and development of data quality solutions including experience leading teams.

Knowledge Preferred:

Demonstrates extensive knowledge and/or a proven record of success in the following areas:

- Performing as a team leader to generate a vision, establishing direction, motivating members, creating an atmosphere of trust, leveraging diverse views, coaching staff, and encouraging improvement and innovation;

- Data wrangling, ETL, data modelling, and business rules codification (e.g. analytics/transformations written in Python/R or similar business rules engines/languages);

- Developing analytics, leveraging tools such as Python, R, open source tooling;

- Data mapping, data flows and governance processes around data management;

- Utilizing data integration tools (e.g. Talend, SnapLogic, Informatica) and data warehousing / data lake tools;

- Understanding database models (NoSQL, relational and other) and associated SQL; and,

- Utilizing API based data acquisition and management.

Skills Preferred:

Demonstrates extensive abilities and/or a proven record of success in the following areas:

- Object-oriented/object function scripting languages Python, R, C/C++, Java, Scala, etc.;
- Relational SQL, distributed SQL and NoSQL databases;
- Big data tools such as Hadoop, Spark, Kafka;
- Data modeling tools such as ERWin, Enterprise Architect, and Visio;
- Data integration tools such as Talend, Informatica, and SnapLogic;
- Data pipeline and workflow management tools Azkaban, Luigi, Airflow;
- Business Intelligence Tools such as Tableau, PowerBI, Zoomdata, and Pentaho;
- Cloud technologies such as SaaS, IaaS and PaaS within Azure, AWS or Google;
- Linux and being comfortable with bash scripting; and,
- Docker and Puppet;

Demonstrates extensive abilities and/or a proven record of success in the following areas:

- Creating design documentation, assisting in project planning, and leading staff in the development of data warehouses, data lakes, and business systems;

- Using written and verbal communication skills to effectively and efficiently translate business requirements into technical specifications and test cases;

- Working with large data sets;

- Leveraging the ability to code data layer services, working with software development teams and data scientists to assist in the broader development of business applications;

- Using agile development processes;

- Using verbal and written communication skills with ability to present technical and non-technical information to various audiences;

- Leading developers code using object oriented design, implementation and maturation to take advantage of the language feature sets;

- Assessing and reviewing code to establish it is efficient code which is concise and best utilizes system resources which can become constrained in a big data environment;

- Utilizing leadership know-how of the open source community, especially working with a large array of open source tools / libraries and languages;

- Building batch data pipeline with relational and columnar database engines as well as Hadoop or Spark, and understands their respective strengths and weaknesses;

- Leveraging computer science fundamentals: data structures, algorithms, programming languages, distributed systems, and information retrieval;

- Possessing an analytical mind with attention to detail and accuracy
- think outside the box;

- Understanding of the security requirements for handling data both in motion and at rest such as communication protocols, encryption, authentication, and authorization; and,

- Utilizing organization and prioritization skills with ability to multitask and switch focus as necessary to meet deadlines and/or with change in priorities.

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