Data Engineering at PwC
Roles, Comp & Culture
An L4 mid data engineer at PwC sits around $154K total comp from 33 verified salary datapoints. The primary Data Engineering tech consists of Azure, Databricks and Data Factory, according to current job listings. PwC pays data engineers in line with other Consulting companies. Reviews put them at 3.7 on Glassdoor, a little below the middle of the pack. PwC employees report healthy morale and employee happiness is trending up over the past year. Layoff risk scores low for the next 30 days. 221 data engineering roles are open right now.
PwC data engineer compensation
Each level's figure is the median of individual PwC offers at that level, so it reflects a typical outcome rather than an average pulled up by a few large packages. Total comp counts base salary plus equity and bonus annualized over the vest, and the range shown is the middle half of offers, with the top and bottom quarters trimmed off.
PwC employee sentiment, tracked weekly
Employee happiness for data engineers over the past year, so you can see which direction it is moving, not just where it sits today.
PwC sits at 3.7 on Glassdoor, a little below the middle of the pack, and Blind sentiment is mixed, which is consistent with what consulting data engineering typically produces: engineers who value variety and client exposure tend to find the rotation rewarding; those who want to own infrastructure through its full lifecycle find the handoff model frustrating. The happiness picture is healthy and trending up, which is better than the cynical read of professional services might suggest. Compensation at $154K for L4 sits in line with other Consulting companies, meaning the firm doesn't compensate for the consulting overhead relative to tech peers. The real trade is career capital in enterprise architecture and stakeholder management against slower comp growth and limited production ownership.
PwC is actively hiring at scale: 221 open data engineering roles across 65 cities, with New York leading. That volume suggests the firm is expanding its data and AI delivery capacity rather than steady-state backfill, likely tracking client demand for Databricks and Azure migrations. The 30-day layoff risk is low, which fits the professional services model where revenue is tied to billable headcount rather than product bets. For someone joining now, the next 12 months look like ramp time on client delivery, with utilization rate as the primary measure. Growth into a senior advisory role is available but not automatic; it depends on client exposure quality as much as technical output.
PwC data engineering tech stack
The languages, storage, and processing tools PwC data engineers actually work with, grouped by what they do. Tailor your system-design answers to this stack.
PwC's data engineering work is shaped by the consulting model: engineers here don't own a single product's pipeline but instead cycle across client engagements, each with its own data problems, compliance requirements, and incumbent stack. The firm's scale in financial services, healthcare, and public sector means the data problems skew regulatory-heavy, where lineage, auditability, and access controls matter as much as throughput. The visible stack, Azure, Databricks and Data Factory, points to a Microsoft-first delivery posture, which holds across most enterprise clients PwC serves. Day-to-day, that translates to building ingestion pipelines, modeling client data warehouses, and advising on architecture choices, then handing the work off rather than running it in production long-term. The job rewards breadth and speed over depth on any single domain.
Data FactoryPwC data engineer job openings
A live read on what they are hiring: open roles, recent postings, where, and at what level.
Architect, design, and develop robust, end-to-end data pipelines utilizing Azure Data Factory, Azure Databricks, and Azure Synapse Analytics BR
In this role, you will have the opportunity to work with a diverse range of clients, helping them to harness the power of data and analytics to achieve their business objectives.
As a Senior Data Engineer - Senior Manager, you will leverage data and analytics to provide strategic insights and drive informed decision-making for clients.
As a Managed Services - Data Engineer - Senior Associate, you will leverage data and analytics to provide strategic insights and drive informed decision-making for clients.
Analyze and address evolving needs within health systems through data insights
As a Tax Innovation & Delivery Experience - Data Engineering - Experienced Associate, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis.
As a Tax Innovation & Delivery Experience - Data Engineering - Director, you will lead the design and development of advanced data solutions, transforming raw data into actionable insights that drive business growth.
As a Tax Innovation & Delivery Experience - Data Engineering - Senior Associate, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis.
As part of the Managed Data, Analytics & Insights team you manage and lead projects related to building the modern data ecosystem and converting insights into strategic opportunities.
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
The salary pool skews toward entry and mid levels, with 21 reports at the junior band and 12 at mid, and only 2 rungs on the ladder here. Engineers early in their careers who want enterprise breadth fast, particularly on Azure-native stacks and large client data warehouse builds, fit well. If you're already senior and expecting a staff or principal track with infrastructure ownership, the consulting engagement model will chafe. Engineers who thrive here are comfortable context-switching across industries and can explain modeling decisions to non-technical clients. If you want to ship a pipeline and then maintain it, this is the wrong environment. If the fit holds, check the salary ladder to calibrate your level before the offer stage, and prep the loop for pipeline architecture, since that's where PwC's screens spend the most time.
Preparing for the PwC loop
The round-by-round process, example questions, and prep plan are on the interview guide.
Compare PwC with other data engineering employers
How the role, pay, and loop stack up against peer companies.
Prepare at PwC interview difficulty
- 01
Reading a solution is not the same as writing one
Every engineer who has frozen on a query they had read a dozen times knows the gap. The only preparation that closes it is producing the answer yourself, under time, before the interview does it for you
- 02
76% of hiring managers reject on the coding task, not the resume
From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice
- 03
5 problem shapes cover 80% of data engineer loops
Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition