At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. As part of the Data and Analytics Engineering team you design and implement thorough data architecture strategies. As a Senior Associate you analyze complex problems, mentor others, and maintain rigorous standards. You focus on building client relationships and developing a deeper understanding of the business context, navigating increasingly complex situations, and growing your personal brand and technical knowledge. Responsibilities - Designing and implementing thorough data architecture strategies - Analyzing complex issues to create innovative solutions - Mentoring and guiding junior team members - Upholding standards in project deliverables - Building and maintaining client relationships - Developing a thorough understanding of the business environment - Managing and navigating complex scenarios effectively - Enhancing personal brand and technical skills What You Must Have - Bachelor's Degree in Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, or Mathematical Statistics - 2 years of experience What Sets You Apart - Certification in Cloud Platforms [e.g., AWS Solutions Architect, AWS Data Engineer, Google Professional Cloud Architect, GCP Data Engineer Microsoft Azure Solutions Architect, Azure Data Engineer Associate, Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies - Developing and documenting data models, data flow diagrams, and data architecture guidelines - Maintaining data architecture compliance with data governance and data security policies - Collaborating with business stakeholders to understand their data requirements - Building, maintaining, and enhancing ETL/ELT pipelines for data ingestion, processing, and storage - Developing and deploying scalable data storage solutions using AWS, Azure and GCP services - Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow - Enhancing Cloud resources for cost, performance, and scalability The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law. PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy. Learn more about how we work: https://pwc.to/how-we-work For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all. Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines #LI-Hybrid #BI-Hybrid

Role Description This is a remote role that may only be hired in the following location(s): North Carolina, Arizona, Texas. We are seeking an experienced Lead Data Engineer to join our Data Platform Engineering Organization and lead the design, development, and modernization of enterprise data platforms that power analytics, reporting, business intelligence, and operational decision-making across the organization. The ideal candidate is a hands-on data engineering leader with expertise in cloud-based data platforms, data warehousing, ETL/ELT development, and modern data engineering practices. This individual will be responsible for delivering scalable data solutions utilizing AWS Services, Snowflake, dbt, Python, SQL, and related technologies while mentoring team members and driving engineering excellence. As part of our growing Cloud Data and AI Platform organization, you will lead and collaborate with a talented team of engineers, product partners, and business stakeholders to deliver enterprise data products and cloud-based data solutions. This role offers the opportunity to mentor engineering talent, drive engineering best practices, and support the adoption of modern data engineering capabilities across the organization. Qualifications - Bachelor's Degree and 6 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines. - OR High School Diploma or GED and 10 years of experience in the same areas. - Advanced experience with cloud platforms such as AWS, Azure, or GCP. - Advanced experience with modern data warehousing and large-scale data processing technologies such as Snowflake, Spark, or equivalent platforms. - Advanced proficiency in Python and SQL. - Advanced experience designing, developing, orchestrating, and supporting ETL/ELT pipelines and data integration solutions using tools such as dbt, Apache Airflow, Astronomer, or equivalent cloud-native data engineering technologies. - Advanced experience with data modeling, data warehousing, and data engineering best practices. - Experience designing, developing, and supporting scalable, reliable, and high-performing data engineering solutions in enterprise environments. - Experience collaborating with business and technology stakeholders to deliver data-driven solutions. - Strong analytical, problem-solving, and communication skills. Requirements - Experience with enterprise ETL/ELT tools such as DataStage, SAP BODS, SSIS, Informatica, or equivalent technologies. - Experience developing and supporting Operational Data Stores (ODS), analytics platforms, and data products. - Experience with Snowflake Cortex, Change Data Capture (CDC), streaming, and real-time data ingestion technologies including Kafka, Amazon Kinesis, Qlik Replicate, Snow pipe Streaming, or equivalent platforms. - Experience integrating data across AWS, on-premises, and Snowflake environments, with exposure to enterprise security, governance, and compliance frameworks. - Experience with Data Vault modeling and modern data warehousing methodologies. - Experience leading technical initiatives, mentoring team members, and promoting engineering best practices. - Experience within Financial Services, Banking, or other highly regulated industries. - Familiarity with Tableau, Power BI, or other analytics and visualization platforms. - Experience using AI-powered development and productivity tools to improve engineering efficiency and delivery outcomes. - AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate or Professional, SnowPro Core Certification, SnowPro Advanced Data Engineer Certification, or equivalent cloud and data platform certifications. Benefits Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits .

Role Description DigitalOcean is expanding its AI Infrastructure layer to support the next generation of AI-driven applications. We are seeking a Senior Engineer 2 to join our AI Inference Data Plane team. In this role, you will be a key technical leader responsible for designing, developing, and delivering high-scale, resilient data plane services that power our "Inference as a Service" offering. - Technical Leadership: Act as a technical leader on the team, driving the end-to-end design, development, and delivery of critical data plane components hosting large generative AI models. - System Design: Architect and refine system design proposals for our high-scale, multi-tenant AI inference cloud ecosystem, ensuring they meet rigorous availability and resiliency standards. - Performance Optimization: Implement and optimize distributed inference hosting using techniques like tensor/data parallelism, KV cache optimizations, and smart routing. - Collaboration: Work cross-functionally with Product Managers, customer-facing teams, and other engineering teams to align technical roadmaps with customer needs. - Distributed Serving at Scale: Build on Kubernetes-native distributed inference frameworks like llm-d (or alternatives such as NVIDIA Dynamo, Ray Serve) to deliver prefill/decode disaggregation, KV-cache-aware routing, tiered prefix caching, and wide expert parallelism for MoE models. - Flow Control & Load Balancing: Solve the distributed-systems problems unique to LLM serving — inference-aware load balancing on queue depth, cache locality, and predicted latency; flow control and fairness across tenants; autoscaling inference pools; and moving gigabytes of KV-cache between prefill and decode instances with negligible overhead. - Open Source Contributions: Contribute upstream to llm-d, vLLM, and the inference gateway ecosystem, and represent DigitalOcean in these communities. - Mentorship: Coach and mentor junior engineers, fostering a culture of technical excellence and continuous improvement. - Operational Excellence: Maintain and operate critical, high-scale services, utilizing observability tools and defining SLOs to ensure superior platform health. Qualifications - Hands-on experience hosting large language or multimodal models using inference engines like vLLM, SGLang, or TensorRT. - Familiarity with distributed inference serving frameworks such as llm-d, NVIDIA Dynamo, or Ray Serve. - Hands-on experience with vLLM or alternatives (SGLang, TensorRT-LLM, TGI, Modular MAX), including internals like continuous batching, paged attention, and prefix caching. - Understanding of why cluster-scale serving is hard: KV-cache locality is partitioned across workers, naive round-robin routing destroys cache hit rates and tail latency, and disaggregated prefill/decode requires fast cross-pod KV transfer (e.g., NIXL). - Merged contributions to vLLM, llm-d, SGLang, or similar projects strongly preferred. - Knowledge of common LLM architectures and optimization techniques (e.g., continuous batching, quantization). - Expert-level proficiency in GoLang or Python and familiarity with gRPC. - Proven experience shipping customer-facing software products and running critical services in a high-scale environment similar to DigitalOcean. - Experience integrating and building with open-source software. Requirements - Compensation Range: $139,200 - $174,000 - This is a remote role. - JR: 2026-7624 - #LI-Remote Benefits - Competitive array of benefits to support employee well-being. - Reimbursement for relevant conferences, training, and education. - Access to LinkedIn Learning's 10,000+ courses for continued growth and development. - Equity compensation to eligible employees, including equity grants upon hire and the option to participate in our Employee Stock Purchase Program.

Role Description Why you will enjoy Mondays again: - Opportunity to work alongside a talented, diverse team in a collaborative and creative environment - Ongoing investment in your growth through training, mentorship, and industry certifications - Hands-on exposure to cutting-edge technologies across multiple industries - Recognition programs and employee awards within an inclusive culture that celebrates great work, including our AI Innovators Program - Remote or hybrid work options - Competitive salary + bonus opportunities - Robust benefits package, matching 401(k) plan, and substantial PTO - Tuition reimbursement A Day in the Life: - Build and migrate large-scale batch data pipelines from legacy data platforms into Databricks. - Develop and optimize production-grade solutions using Python, Spark, and advanced SQL. - Support parallel legacy and cloud data environments throughout the migration and validation process. - Serve as a subject matter expert while remaining hands-on with day-to-day development and troubleshooting. - Actively use AI tools, including Claude through our Anthropic partnership, to streamline tasks, improve the quality of your work, and share best practices with teammates while continuously seeking new ways to integrate AI into your everyday workflows. - Lead technical design conversations and guide implementation within an established architecture and project framework. - Collaborate with developers, architects, and business stakeholders to communicate technical decisions, risks, and progress. - Improve pipeline reliability and performance through testing, monitoring, tuning, and production support. - Use GitHub Copilot when helpful to support development productivity. - Participate in a rotating on-call schedule approximately every four to six weeks. Qualifications - Recent hands-on experience building production batch solutions in Databricks, ideally within the past 12–18 months. - Strong development experience with Python and Apache Spark. - Advanced SQL skills, including complex query development and performance tuning. - Consultative approach and problem-solving skills to successfully align digital solutions with long-term business goals of the client. - Experience delivering large-scale migrations from legacy data platforms to cloud-based environments, preferably involving Teradata or a comparable platform. - Experience supporting legacy and cloud systems operating in parallel during a migration. - The ability to lead design and technical-direction discussions while remaining actively involved in coding and implementation. - Hands-on experience using AI tools to enhance daily work, or a strong desire to do so, including a willingness to experiment, learn, and champion AI adoption within your role. - Strong communication skills across technical teams, architects, business partners, and leadership. - Availability to participate in an on-call rotation. - Experience with Azure data services—such as Data Factory, Synapse Analytics, Event Hubs, Delta Lake, Cosmos DB, and Azure DevOps—is preferred. - Exposure to Big Data technologies, NoSQL databases, Git, Jenkins, CI/CD practices, and Agile delivery methodologies is a plus. Equal Employment Opportunity Policy Sparq is proud to offer equal employment opportunity without regard to age, color, disability, gender, gender identity, genetic information, marital status, military status, national origin, race, religion, sexual orientation, veteran status, or any other legally protected characteristic. We are committed to providing equal employment opportunities and believe in an inclusive workplace. If you require reasonable accommodations to participate in the job application or interview process, please let us know by contacting recruiting@teamsparq.com . #LI-REMOTE