Title: Senior Data Engineer - PGIM Technology (Hybrid - Newark, NJ) locations Newark, NJ, USA time type Full time job requisition id R-124458 Job Classification: Technology - Engineering & Cloud As an AI/Data Engineer, you will design, build, and maintain scalable data and AI solutions supporting business and analytics needs on modern cloud platforms. You will work closely with senior engineers, architects, and business stakeholders to develop data pipelines, enable analytics, and integrate AI capabilities into applications. This role will focus on hands-on engineering, including data ingestion, transformation, and enabling AI use cases such as semantic search and Retrieval-Augmented Generation (RAG). You will contribute to building reusable data frameworks and accelerating adoption of cloud-native data and AI technologies. This role is based in our office in Newark, NJ following a hybrid work structure with on-site presence required 3 days per week. What you can expect: - Build and maintain scalable data pipelines (ETL/ELT) - Develop solutions using Microsoft Fabric, Azure Data Factory, or similar - Implement data quality checks, transformations, and data modeling - Work with large-scale datasets using PySpark / SQL - Deploy and integrate machine learning models into pipelines - Develop AI-powered solutions (semantic search, embeddings, RAG) - Build and expose data and AI services via APIs - Contribute to CI/CD pipelines using GitHub Actions or Azure DevOps - Implement best practices for data security, governance, and access - Monitor and troubleshoot pipelines and AI systems - Collaborate with analysts, scientists, and stakeholders - Contribute to documentation and reusable components What you will bring: - Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field - 3–6 years of experience in data/AI engineering - Strong Python and SQL skills - Experience with data pipeline tools (ADF, Fabric, AWS Glue, etc.) - Experience with Spark/PySpark - Familiarity with data lakes and warehouses - Experience deploying ML models - Basic MLOps understanding - Exposure to Generative AI (embeddings, RAG, LLM APIs) - Experience with REST APIs and microservices - Familiarity with CI/CD and Git - Understanding of data governance and security - Strong problem-solving and communication skills *PGIM welcomes all applicants, even if you don't meet every requirement. If your skills align with the role, we encourage you to apply. Note: Prudential is required by state specific laws to include the salary range for this role when hiring a resident in applicable locations. The annual base salary range for this role is from $115,000 to $155,000. Specific pricing for the role may vary within the above range based on many factors including geographic location, candidate experience, and skills. What we offer you: - Market competitive base salaries, with a yearly bonus potential at every level. - Medical, dental, vision, life insurance, disability insurance, Paid Time Off (PTO), and leave of absences, such as parental and military leave. - 401(k) plan with company match (up to 4%). - Company-funded pension plan. - Wellness Programs including up to $1,600 a year for reimbursement of items purchased to support personal wellbeing needs. - Work/Life Resources to help support topics such as parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development. - Education Benefit to help finance traditional college enrollment toward obtaining an approved degree and many accredited certificate programs. - Employee Stock Purchase Plan: Shares can be purchased at 85% of the lower of two prices (Beginning or End of the purchase period), after one year of service. Eligibility to participate in a discretionary annual incentive program is subject to the rules governing the program, whereby an award, if any, depends on various factors including, without limitation, individual and organizational performance. Prudential Financial, Inc. of the United States is not affiliated with Prudential plc. which is headquartered in the United Kingdom. Prudential is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender identity, national origin, genetics, disability, marital status, age, veteran status, domestic partner status, medical condition or any other characteristic protected by law.

Role Description Appfire is seeking an experienced full-time Senior Analytics Engineer! In this role you will build, define and activate Appfire’s company-wide data asset (Snowflake) from ground up data sources. You will work with stakeholders across Appfire to integrate, test, connect, and build brand new data and metrics within our Snowflake metrics layers, achieving a trusted, accessible and well-defined view of information across the company. Our Analytics Engineers build metric foundations for reporting, analysis and experimentation, pushing the boundaries of decisions across the company under an aligned view of the world. They leverage their expertise in metric development, DBT, data modeling, SQL and Python. Using these skills you will transform data from raw data warehouse into data artifacts powering impactful analytic use cases (e.g. metrics, dashboards, adhoc analysis and self-service solutions) that enable and push the boundaries of decisions across the company. As an Analytics Engineer you will sit at the intersection of business and data, working collaboratively to enable and achieve meaningful outcomes by evolving our ecosystems to scale impact. We’re growing quickly and have a lot to accomplish. What You Will Do: - Understand decision needs by interfacing with fellow Analytics Engineers, Data Engineers, Data Analysts and Business Partners - Architect, build, and launch efficient & reliable data models and pipelines in partnership with Data Engineering, leveraging DBT and Snowflake - Design and implement metrics and dimensions enabling self-service analysis and structured views of Appfire’s KPI’s that scale trust, accountability and decision impact - Define and share best practices on metric, dimension, and data model development and definitions for analytics use cases Qualifications - 5+ years of relevant industry experience - Passion for high data quality and impactful analytics engineering work - Expert SQL skills for data modeling and query optimization - Extensive experience with self service, advanced analytics, semantic and metrics layers - 3+ Years of Experience with Python and DBT - Strong understanding of data warehousing concepts and best practices - Efficient problem-solving and analytical skills - Proven ability to succeed in both collaborative and independent work environments at a remote-work company - Proven experience managing concurrent complex data projects from start to finish - Continuous learner with an eye on industry trends and new technologies - Excellent communication and documentation skills with the ability to explain technical concepts to a non-technical audience - Ability to effectively leverage AI tools and techniques to enhance dbt development, increase efficiency, and strengthen documentation Requirements - Experience with dbt (Data Build Tool) and its implementation for data transformation and modeling - Proven experience with data wrangling and designing/developing experience owning end to end SDLC and implementation, with full ownership of stakeholder management and expectation setting, prioritization, development and delivery - Proficiency in source code management tools such as GIT, BitBucket, etc. - Experience working with Cloud Technologies (AWS/GCP/Azure) - Experience working with various semi structured data formats (ex. JSON) - Experience building data solutions for future scale and analytics use-cases - 3+ years of development experience on industry standard BI tools - ML analytics engineering experience a plus - Marketing Analytics experience a plus Benefits - Every Appfire team member is eligible for company equity, fostering a genuine sense of ownership and shared success as we continue to grow - Unlimited Paid Time Off (PTO) - 10 paid company holidays annually - Medical insurance fully covered by Appfire (100% employer-paid) - Dental insurance with costs shared 50/50 between Appfire and employees - Vision insurance - Group Term Life Insurance - Voluntary Life Insurance - Critical Illness coverage - Accident Insurance - Long-Term Disability coverage - Employee Assistance Program (EAP) - Fitness and wellness reimbursements through our benefits provider - Grow your skills and advance your career through Appfire University, our custom on-demand learning platform designed to support continuous professional development - Every employee receives three fully paid volunteer days per year to participate in our Corporate Social Responsibility (CSR) initiatives and support local communities - Flexible Spending Accounts (FSA) - Monthly remote-work stipend - Dedicated Amazon account for ordering approved equipment and peripherals - Competitive 401(k) plan with company matching to help build long-term financial security Company Description Appfire has been consistently recognized for company growth, culture, corporate social responsibility, and product excellence and has been included among the Deloitte Technology Fast 500, Inc. Best Workplaces, BuiltIn Best Places to Work, and Inc. 5000.

• Capture & Ingestion: Own the full capture path from wire to lake • Build batch + stream pipelines (Airflow, Spark, dbt) for tick and reference data • Own L2/L3 order-book reconstruction with gap handling • Storage & Modeling: Own the Iceberg-over-S3 lakehouse • Drive storage cost optimisation via compaction, tiering, and snapshot expiry • Tooling & Libraries: Build libraries for schema management, data contracts, validation, and lineage • Reliability & Observability: Embed monitoring, alerting, SLAs/SLOs, and CI/CD across capture and pipeline layers on Kubernetes • Collaboration: Partner with Quant Research, Data Science, Backend, and DevOps to translate requirements into platform capabilities

• Lead, design, and scale data solutions to support Journey Analytics initiatives, focusing on code quality, reusability, and reliable data platforms. • Set the technical direction, overseeing the evolution of data architectures. • Lead a team of data engineers to deliver high-quality, performant datasets for analytics and reporting use cases. • Mentor a team of data engineers, fostering best practices in coding, architecture, and data engineering standards. • Drive the technical strategy for Journey Analytics data platforms, ensuring scalability, maintainability, and performance. • Oversee maintenance, optimization, and automation of code repositories in GitHub. • Guide the refactoring of legacy codebases to improve maintainability, scalability, and reusability. • Drive the design and implementation of modular, reusable data components. • Oversee development and management of automated data pipelines in Databricks. • Ensure data quality, governance, performance, and reliability across all data pipelines and datasets.