Asset Performance and Data Engineer supporting data insights, reporting, and improved asset information for Network Assets at ESB. Driving SAP and asset catalogue improvements for high - quality data management.
About the role
- Data Engineer designing and building data pipelines for PG&E's reliability initiatives. Engaging in continuous improvement and collaborating with various stakeholders in hybrid role.
Responsibilities
- Designs, develops, modifies, configures, debugs and evaluates jobs for extracting data from various sources
- Implements transformation logic, and stores data in various formats fit for use by stakeholders
- Collects metadata about jobs including data lineage and transformation logic
- Works with teams, clients, data owners, and leadership throughout the development cycle practicing continuous improvement
- Assembles large, complex sets of data that meet non-functional and functional business requirements
- Builds high-performance data pipelines and prototypes that enable business use of the data
- Builds infrastructure for optimal extraction, transformation and loading of data from various data sources
- Understands business requirements and applies them to complex software engineering and analysis
- Communicates (oral and written) recommendations with peers inside the department
- Partners with team members to understand and incorporate standards information and requirements into work procedures
- Identifies and analyzes to departmental standards, norms, and new goals/objectives
- Assists in data, design, product, and executive teams with data-related technical issues
- Understands the infrastructure that allows big data to be accessed and analyzed
- Utilizes department standard issue tracking, source control, and documentation tools.
Requirements
- Bachelors Degree in Computer Science or job-related discipline or equivalent experience
- Masters Degree in Computer Science or job-related discipline or equivalent experience preferred
- 1 year of experience with data engineering/ETL ecosystem, such as Palantir Foundry, Spark, Informatica, SAP BODS or OBIEE
- Experience with data engineering and data transformations via a training or apprenticeship program acceptable
- Business Intelligence and data access tool knowledge
- Knowledge of software engineering principles such as unit testing, CI/CD, source control.
Benefits
- This job is also eligible to participate in PG&E’s discretionary incentive compensation programs.
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Senior Test Data Engineer creating non‑production test data ecosystem at Signet Jewelers. Designing modern TDM practices and building automation for data provisioning and monitoring.
Full Stack Data Engineer responsible for building and optimizing data pipelines and lakehouse architectures. Collaborating with teams to ensure data quality and delivering analytics - ready datasets.
Participating in designing and developing data platforms for CVS Health's extensive healthcare data. Collaborating with teams to optimize data workflows and ensure data quality in a high - volume environment.
Data Engineer supporting Department of Defense programs by designing and maintaining scalable ETL pipelines. Collaborating with cross - functional teams and ensuring data integrity in analytics solutions.
Lead Data Engineer overseeing ETL processes and data management at AI & Data Engineering team in Pune, India.
Data Engineer building and maintaining Azure data pipelines for analytical use cases at Manulife. Collaborating with teams to support business while aligning with IT security.
AI/ML/Data Engineer building production - grade AI solutions for Bragg's iGaming platform. Collaborating with teams to develop innovative data infrastructures and ML models.
Principal Data Architect delivering IT solutions for Waste Management's IT architecture needs. Focus on software development, integration, and mentoring team members.
Data Engineer developing data pipelines for a top 10 national professional services firm, managing cloud engineering solutions across Azure and Databricks with a collaborative team.