> Markdown version of [/jobs/ext/542010-it-engineer-principal-ii-data-analytics](https://www.wearedevelopers.com/jobs/ext/542010-it-engineer-principal-ii-data-analytics). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # IT Engineer Principal II -Data & Analytics - **Company:** Public Service Enterprise Group Incorporated - **Location:** Newark, NJ, United States (Remote available) - **Experience:** Expert - **Salary:** $121,200.0 - $199,200.0 - **Contract:** Permanent contract - **Skills:** Adobe InDesign, Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Data Analysis, Automation of Tests, Business Intelligence Development, Data as a Services, Data Validation, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, DevOps, Digital Assets, Metadata, Meta-Data Management, Operational Databases, Software Engineering, PL-SQL, SQL Databases, SQL Server Integration Services, Data Streaming, Azure Data Factory, Generative AI, Data Lakes, Information Technology, AWS Glue, Data Analytics, Non-relational Database, Data Management, Machine Learning Operations, Software Version Control, Data Pipelines - **Published:** June 11, 2026 - **Apply:** https://www.juju.com/job/00000000g733mq ## About the Role + Bachelor's degree in Computer Science or a related technical field. + 8-12 years of experience delivering technology solutions, preferably with a focus on data engineering, analytics engineering, or data integration. + Demonstrated leadership through ownership of technical solutions or project components. + Experience documenting technical solutions, data flows, and system behavior. + Foundational knowledge of data management practices and familiarity with data warehouse and data lake architectures. + Strong ability to design, build, and manage data pipelines including transformations, data modeling, metadata, and workload management. + Experience with AWS and/or Microsoft analytics platforms and related data services. + Proficiency with SQL, PL/SQL, and experience working with relational and non relational databases. + Experience supporting DevOps practices such as version control, automated testing, and release processes. + Experience collaborating with BI and advanced analytics teams and supporting their data needs. + Experience developing and maintaining ETL/ELT pipelines using tools such as SSIS, AWS Glue, Azure Data Factory, or similar. + Compliance with the Department of Energy's regulation 10 CFR 810 is required. Desired + Experience supporting machine learning workflows, including feature pipelines or model deployment. + Familiarity with emerging analytics and AI technologies, including generative AI or retrieval based approaches. + Experience with data governance, data quality frameworks, or responsible AI practices. + Exposure to modern data engineering or analytics tools and techniques. ## Description The Principal 2 IT Engineer - Data & Analytics plays a key role in delivering and maintaining the data assets required for enterprise reporting, analytics, automation, and AI initiatives. The role focuses on designing, building, optimizing, and supporting data pipelines, curated datasets, and related data engineering components that serve analysts, data scientists, and business users across the company. This engineer participates in design, development, testing, deployment, and production support of data solutions, working closely with business analysts, product managers, and technical partners to ensure reliability, quality, and consistent delivery. Job Responsibilities + Analyze business and end-user requirements and design, configure, develop, and test the data pipelines, transformations, and data models needed for reporting, analytics, and operational use cases. + Create, maintain, and optimize data pipelines as workloads move from development into production, ensuring they perform reliably and efficiently. + Develop and maintain documentation such as data flow diagrams, technical specifications, and process descriptions to support understanding, maintainability, and knowledge transfer. + Work closely with business analysts, BI developers, data scientists, and other data consumers to refine data needs and ensure solution outputs meet functional expectations. + Coordinate with enterprise architects, cloud and infrastructure teams, software development teams, and cybersecurity to ensure data engineering solutions align with enterprise standards and integrate appropriately with other technology areas. + Participate in design reviews and change reviews, offering input to help ensure quality, consistency, and conformance with established engineering practices. + Provide support for production data pipelines and analytics systems, including troubleshooting issues, implementing fixes, performing proactive maintenance, and conducting root-cause analysis as needed. + Assist with controlled deployments, upgrades, updates, and enhancements following standard change-management processes and ensuring readiness for production. + Review existing tools, platforms, and processes to evaluate performance, scalability, and alignment with business needs, making recommendations for improvements when appropriate. + Contribute to ongoing data management practices, including metadata management, data quality checks, governance adherence, and structured documentation. + Support continuous improvement of engineering methods, coding standards, automation opportunities, and collaboration practices that strengthen the data engineering discipline. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [A Guide to Green Tech and Green IT Careers](https://www.wearedevelopers.com/magazine/374-a-guide-to-green-tech-and-green-it-careers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)