Data Engineer I (II)

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

• 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

• 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