• Design, develop, and maintain large-scale data systems • Develop and implement ETL processes using various tools and technologies • Collaborate with cross-functional teams to design and implement data models • Work with big data tools like Hadoop, Spark, PySpark, and Kafka • Develop scalable and efficient data pipelines • Troubleshoot data-related issues and optimize data systems • Transition and upskill into Databricks & AI/ML projects

The Opportunity As a Data Engineer - Senior Associate, 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. As a Senior Associate, you will build meaningful client connections and learn how to manage and inspire others. You will navigate increasingly complex situations, grow your personal brand, and deepen your technical skills. You are expected to anticipate the needs of your teams and clients, and to deliver quality work. Embracing increased ambiguity, you will be comfortable when the path forward isn't clear, using these moments as opportunities to grow. In this role within our Technology Consulting practice, you will leverage advanced technologies and techniques to design and develop robust data solutions for clients. You will transform raw data into actionable insights, enabling informed decision-making and driving business growth. By using a broad range of tools, methodologies, and techniques, you will generate new ideas and solve problems, contributing to the overall strategy and objectives of your projects. This position offers a chance to develop a deeper understanding of the business context and how it is evolving. Responsibilities - Designing and implementing data infrastructure and systems to facilitate efficient data processing and analysis - Developing and maintaining data pipelines, integration, and transformation solutions to support client needs - Utilizing Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities - Applying data architecture development and database management skills to optimize data solutions - Leveraging Apache Airflow and Apache Hadoop for scalable data processing and workflow management - Building and managing data lakes and warehouses to support large-scale data storage and retrieval - Confirming data quality and validation through rigorous testing and performance tuning - Collaborating with clients to understand their data requirements and deliver actionable insights - Utilizing Databricks Unified Data Analytics Platform for advanced data analytics and visualization - Implementing data security best practices to protect sensitive information and maintain compliance - Applying dimensional modeling and directed acyclic graphs (DAGs) for efficient data organization and processing - Supporting the development of data strategies to drive business growth and informed decision-making What You Must Have - At least a Bachelor's degree - At least 2 years of experience What Sets You Apart - Preference for at least one of the following fields of study: Management Information Systems, Computer and Information Science, Systems Engineering, Electrical Engineering, Chemical Engineering, Industrial Engineering, Mathematics, Statistics, Mathematical Statistics - Demonstrating proficiency in data engineering platforms like Databricks - Utilizing cloud platforms such as AWS and Microsoft Azure - Excelling in data architecture development and data modeling - Implementing data pipeline and data integration strategies - Navigating complex data environments with Apache Hadoop and Airflow - Applying critical thinking to solve data-related challenges 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

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. Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member's unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same. Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Analyse and identify the linkages and interactions between the component parts of an entire system. Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion. Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables. Develop skills outside your comfort zone, and encourage others to do the same. Effectively mentor others. Use the review of work as an opportunity to deepen the expertise of team members. Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate. 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 can design and implement thorough data architecture strategies that meet current and future business needs. As a Manager you can lead the development of data models, support compliance with data governance policies, and collaborate with business stakeholders to translate data requirements into technical solutions. You can also build and enhance ETL/ELT pipelines, manage data warehouses and data lakes, and implement data security practices. Responsibilities - Design and implement thorough data architecture strategies - Lead the development of data models - Achieve compliance with data governance policies - Collaborate with business stakeholders to translate data requirements - Build and enhance ETL/ELT pipelines - Manage data warehouses and data lakes - Implement data security leading practices - Foster a culture of data-driven decision making 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 - 5 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, or Snowflake Core, Snowflake Databricks Data Engineer Associate] is a plus - Designing and implementing thorough data architecture strategies that meet the current and future business needs - Developing and documenting data models, data flow diagrams, and data architecture guidelines - Verifying data architecture is compliant with data governance and data security policies - Collaborating with business stakeholders to understand their data requirements and translate them into technical solutions - Evaluating and recommending new data technologies and tools to enhance data architecture - Building, maintaining, and improving ETL/ELT pipelines for data ingestion, processing, and storage across batch and real-time data processing - Building, maintaining, and improving Data Quality rules leveraging DQ tools and/or other ETL/ELT tools - Developing and deploying scalable data storage solutions using AWS, Azure and GCP services such as S3, Amazon RDS, DynamoDB, Azure Data Lake Storage, Azure Cosmos DB, Azure SQL DB, GCP Cloud Storage etc. - Implementing data integration solutions using AWS Glue, AWS Lambda, Azure Data Factory, Azure Functions, GCP Functions, GCP Dataproc, Dataflow and other relevant services - Designing and managing data warehouses and data lakes, verifying data is organized and accessible - Monitoring and troubleshooting data pipelines, data warehouses and workflows to verify data quality, system reliability, performance and cost management - Implementing IAM roles and policies to manage access and permissions within AWS, Azure, GCP - Use AWS CloudFormation, Azure Resource Manager templates, Terraform for infrastructure as code (IaC) deployments - Use AWS, Azure and GCP DevOps services to build and deploy DevOps pipelines - Implementing data security practices using AWS, Azure, GCP, Snowflake or Databricks - Improving Cloud resources for cost, performance, and scalability - Proficiency in SQL and experience with relational databases - Proficient in programming languages such as Python, Java, or Scala - Familiarity with big data technologies like Hadoop, Spark, or Kafka is a plus - Experience with machine learning and data science workflows is a plus - Knowledge of data governance and data security practices - Demonstrating analytical, problem-solving, and communication skills - Having the ability to work independently and as part of a team in a fast-paced environment - Applying modern, cloud-based technology skills, ability to research emerging trends, analyst publications, and adoption of modern technologies in solution architectures - Collaborating and contributing as a team member: understanding personal and team roles, contributing to a positive working environment by building proven relationships with team members, proactively seeking guidance, clarification and feedback - Prioritizing and handling multiple tasks, researching and analyzing pertinent client, industry and technical matters, utilizing problem-solving skills, and communicating effectively in written and verbal formats to various audiences (including various levels of management and external clients) in a professional business environment - Coaching and collaborating with associates who assist with this work, including providing coaching, feedback and guidance on work performance The salary range for this position is: $99,000 - $232,000. 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 We are seeking an experienced and visionary Staff Engineer to technically anchor our new AI Data Engine team. This pivotal role will drive the technical strategy, architecture, and execution of initiatives aimed at significantly accelerating our ML dataset generation and our data warehouse stack. The ultimate goal is to drastically reduce the development cycle for new pipelines, ML models and get us operationally prepared for a driverless future! You will be a hands-on technical leader, blending deep expertise in data systems and infrastructure with the ability to architect complex, highly scalable solutions. While this is an individual contributor role, you will act as a force multiplier—mentoring a high-performing team of engineers, setting rigorous technical standards, and fostering a culture of engineering excellence, innovation, and continuous improvement. What You'll Be Doing - Technical Leadership & Mentorship: - Serve as the technical anchor for a high-performing team of data and infrastructure engineers building out Motional’s Data Stack. - Influence the technical roadmap, architectural priorities, and project scoping in alignment with broader engineering objectives. - Provide deep technical guidance, peer mentorship, and establish rigorous engineering standards and best practices for the team. - Architecture, Strategy & Execution: - Define and execute the technical vision and architecture for storing metrics and generating ML datasets for large computer vision and behavioral models. - Identify, evaluate, and prototype cutting-edge technologies and methodologies for speeding up data loaders for training, ingestion of metrics, and querying of large datasets for everything from dashboards to training. - Act as a hands-on contributor for the most complex, high-impact architectural challenges within the data engine space. - Cross-functional Collaboration: - Collaborate closely with ML research, ML Training platform, and data engineering teams to understand their requirements, co-design scalable architectures, and integrate solutions seamlessly. - Drive technical consensus and communicate complex architectural concepts and strategies to both technical and non-technical stakeholders. Qualifications - BS or MS in Computer Science or related field - 6+ years of professional experience in data platform engineering - 3+ years of experience in a technical lead, staff engineer, or senior architecture role, with a proven track record of driving cross-team technical initiatives and mentoring senior engineers. - Extensive experience with managing large (petabyte plus) scale data platforms such as data warehouses, object storage, and ML training data stores. - Extensive experience with workflow orchestration frameworks such as Airflow or Step Functions. Technical Skills - Core Programming: Strong programming skills in Python. C++ experience is a plus. - Agentic AI & LLMOps: Proven experience designing, building, and deploying agentic workflows and multi-agent systems using frameworks like LangChain, LlamaIndex, DSPy, or custom LLM orchestration tools for reasoning and automated data processing. - Storage & Vector Ecosystems: Knowledge of modern data storage formats (Parquet, Iceberg) and vector databases (LanceDB, Milvus, Qdrant) and retrieval architectures (RAG) to manage massive multimodal datasets (video, sensor data, text). - Cloud & Infrastructure: Strong knowledge of cloud infrastructure (AWS, GCP) solutions, distributed compute, and scalable model serving. - Domain Experience: Prior experience building data warehouses, lakehouse architectures, or active-learning data loops at an advanced machine learning, robotics, or autonomous vehicle company. Bonus Points (not required) - Prior experience in autonomous vehicles (AV) is a plus. - Prior experience with Bazel based build systems. Benefits - Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more. Salary Range $172,000 — $229,000 USD