*Flexible Work Arrangement: Hybrid*
The Data Engineer is responsible for designing and implementing methods to improve data: reliability, security and quality across the enterprise. They combine raw information from different sources to create consistent and machine-readable formats. They also develop, test and build algorithms, architectures and infrastructure that enable data extraction and transformation for various modeling needs; for example predictive or prescriptive modeling.
Essential Functions:
Analyze and organize raw data, cataloging fields and entities
Building data architectures and data pipelines to collectively bring together data
Analyzing, planning, and defining data architecture framework(s), including security, reference data, metadata, and master data
Participation in analyzing business needs and objectives with analysts, data Architects and engineers, developers, report writers and report consumers
Inform and support the organizations data strategy
Conduct data analysis and collaboration with analysts, developers and business users
Build algorithms and prototypes to support data integration and other data related functions
Identify opportunities for data acquisition and determine data update velocity
Collaborating with other teams within the organization to devise and implement data strategies, build models, and assess business partners needs and goals
Work with Data Architects in developing and supporting patterns that data engineers, developers and others can follow
Support and inform data governance practices
Create and implement data management processes and procedure
Characteristics & Qualifications:
Required:
Bachelor's Degree in Computer Science or Information Systems, or 0-5 years of experience in a Data Engineer role
0-5 years of experience with SQL
Ability to produce high-quality work products with attention to detail
Ability to visualize and solve complex problems
Ability to apply analytical and mathematical solutions
Strong knowledge of SQL Knowledge of algorithms, data structures, complexity analysis and software design
Knowledge of managing application configurations Knowledge of Unix, AIX, Debian, Windows operating systems, containers, container orchestrators
Knowledge of git based code repositories
Preferred:
Master's Degree in Computer Science
0-5 years of experience with programming e.g. SAS, Python, PySpark
0-5 years of experience with Alteryx or Qlik Replicate
0-5 years of experience with data pipeline and data workflow management tools
0-5 years of experience in Big Data technologies (e.g. Spark, Databricks)
0-5 years of experience building and optimizing 'big data' data pipelines, architectures, and data sets
0-5 years of experience with NoSQL
0-5 years of experience in Azure data engineering and cloud data processing services
Experience with PJM operations, markets, and planning functions
Experience with Alteryx, SSIS or Qlik Replicate
Experience with one or more of the following: Java, Python or C#
Experience with visualization and reporting tools such as Tableau, Qlik etc.
Experience in end to end delivery and lifecycle of analytical business solutions
Similar Jobs
What We Do
PJM Interconnection manages the high-voltage electric system that provides power to 65 million people in all or parts of 13 states and the District of Columbia. It's the largest power grid in North America.
As a neutral, independent party, PJM administers a competitive wholesale electricity market. PJM’s long-term regional planning process provides a broad, interstate perspective that identifies the most effective and cost-efficient improvements to the grid to ensure reliability and economic benefits.
PJM serves all or parts of Delaware, Illinois, Indiana, Kentucky, Maryland, Michigan, New Jersey, North Carolina, Ohio, Pennsylvania, Tennessee, Virginia, West Virginia and the District of Columbia.
An independent board oversees PJM’s activities. Effective governance and a collaborative stakeholder process help PJM achieve its vision: “To be the electric industry leader – today and tomorrow – in reliable operations and efficient wholesale markets.”
