Developer-Senior Associate-Analytics As Service - Operate

At PwC, our people in managed services focus on a variety of outsourced solutions and support clients across numerous functions. These individuals help organisations streamline their operations, reduce costs, and improve efficiency by managing key processes and functions on their behalf. They are skilled in project management, technology, and process optimization to deliver high-quality services to clients. Those in managed service management and strategy at PwC will focus on transitioning and running services, along with managing delivery teams, programmes, commercials, performance and delivery risk. Your work will involve the process of continuous improvement and optimising of the managed services process, tools and services.

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.

Skills

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 Firms code of conduct, and independence requirements.
  
  

Data Engineer – Senior Associate (5–9 Years)

Our Analytics & Insights Managed Services team brings a unique combination of industry expertise, technology, data management and managed-services experience to create sustained outcomes for our clients and improve business performance. We empower companies to transform their approach to analytics and insights while building your skills in exciting new directions. Have a voice at our table to help design, build and operate the next generation of software and services as a Data Engineer.

Basic Qualifications

Job Requirements and Preferences

• Minimum Degree Required: Bachelors degree in computer science, Data Engineering, Information Systems, or a related technical field
• Minimum Years of Experience: 5–9 years of hands-on experience designing, building, and operating data platforms and pipelines
  
  

Preferred Qualifications

• Degree Preferred: Masters degree in data science, Analytics, Computer Science, Information Systems, or related discipline
• Preferred Fields of Study: Data Processing/Analytics/Science, Management Information Systems, Software Engineering
  
  

Preferred Knowledge & Skills

As a Senior Associate, you’ll take ownership of complex data solutions, drive best practices, and mentor junior teammates across the full data lifecycle:

• Advanced Data Pipeline Development – Architect and implement scalable ETL/ELT workflows using Python (PySpark), Scala, and SQL – Orchestrate batch and real-time jobs with Airflow, Prefect, or Apache NiFi
• Big Data & Streaming Ecosystems – Develop Spark applications and manage Hadoop components (HDFS, YARN) for large-scale processing – Build and integrate streaming solutions using Kafka, Kinesis, or Pulsar
• Cloud & Hybrid Infrastructure – Deploy and operate data platforms on OCI/Azure/GCP (e.g., ADLS, Glue/Dataflow, Databricks clusters) – Automate provisioning with Terraform or CloudFormation; containerize workloads with Docker/Kubernetes
• Data Modeling & Warehousing – Design dimensional and normalized schemas for data lakes and warehouses (Snowflake, Redshift, BigQuery, Dataiku) – Implement partitioning, clustering, and indexing strategies to optimize query performance
• DevOps & Automation – Build CI/CD pipelines for data code and infrastructure using GitHub Actions, Jenkins, or GitLab CI – Automate testing, monitoring, and rollback with tools like Great Expectations, Prometheus, and Grafana
• Data Governance & Quality – Establish lineage, metadata management, and quality checks (e.g., Deequ, Great Expectations) – Partner with data stewards to enforce access controls, compliance, and cataloging
• Performance Tuning & Scalability – Profile and optimize Spark jobs, SQL queries, and storage layouts to meet SLA requirements – Apply caching, parallelism, and resource-management best practices
• Collaboration & Leadership – Translate complex technical designs into clear recommendations for business and IT stakeholders – Mentor and coach junior engineers, lead code reviews, and champion best practices
• Accelerators & Innovation – Contribute to reusable playbooks, reference architectures, and “starter kits” that accelerate delivery – Stay current with emerging data technologies and drive continuous improvement

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