Associate Principal​/Programmatic AdTech Engineer; Forensic Services practice

Position Overview

CRA’s practice supports companies’ commitment to integrity by assisting them and their counsel in independently responding to allegations of fraud, waste, abuse, misconduct, and non‑compliance. We are noted for deploying cross‑trained teams of forensic professionals to assist our clients in gaining deeper insights and greater value more quickly. We provide accounting and forensic services as well as cybercrime investigation services.

• Lead and support technical vision and execution for forensic investigations of advertising technology systems, privacy compliance, and data flows across web, mobile, and programmatic platforms.
• Reverse‑engineer complex AdTech products, programmatic supply chains, tracking tools, identity graphing frameworks, real‑time bidding systems, and monetization controls.
• Design and build forensic data pipelines, processing infrastructure, and investigatory tools used to process and analyze large‑scale datasets (bid streams, impression logs, consent records).
• Deploy AI and advanced tooling to support investigations, detect privacy compliance gaps, develop compliant data monetization strategy.
• Serve as technical subject matter expert advising legal counsel and corporate executives on complex data, engineering, privacy, and AdTech challenges—translating complex technical findings into actionable business insights.
• Lead cross‑functional engagements requiring coordination across technical analysis, legal strategy, data engineering, and stakeholder communication under aggressive deadlines.
• Mentor junior team members.
• Contribute to internal initiatives.

• Bachelor's degree required;
  Computer Science, Software Engineering, Data Science, Information Systems or related technical field.

• 8-10+ years in software engineering, progressive experience with at least two of the following domains:
  Programmatic advertising technology, marketing technology platforms, or digital media ecosystems;
  Data engineering, analytics engineering, or large‑scale data pipeline development;
  Privacy engineering, compliance technology, or regulatory risk assessment;
  Consulting delivery, expert services, or client‑facing technical advisory roles.
• Representative portfolio projects, open source contributions, and/or other observable works.
• Deep understanding of programmatic advertising architectures including supply‑side platforms (SSPs), demand‑side platforms (DSPs), data management platforms (DMPs), customer data platforms (CDPs), and ad exchanges.
• Knowledge of real‑time bidding protocols, OpenRTB specifications, header bidding mechanics, prebid.js, and programmatic supply chain data flows.
• Understanding of identity graph methodologies including deterministic matching, probabilistic linkage, device graphs, and privacy‑preserving cohort approaches.

• Deep understanding of programmatic advertising architectures including supply‑side platforms (SSPs), demand‑side platforms (DSPs), data management platforms (DMPs), customer data platforms (CDPs), and ad exchanges.
• Knowledge of real‑time bidding protocols, OpenRTB specifications, header bidding mechanics, prebid.js, and programmatic supply chain data flows.
• Understanding of identity graph methodologies including deterministic matching, probabilistic linkage, device graphs, and privacy‑preserving cohort approaches.
• Advanced proficiency in at least two programming languages:
  Python, SQL, R, JavaScript, or similar languages applicable to data analysis and tool development.
• Experience with data engineering frameworks and tools:
  Apache Spark, Airflow, and modern data warehousing platforms (Snowflake, Big Query, Redshift).
• Competency in data manipulation, transformation, and analysis using pandas, Num Py, or equivalent libraries.
• Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure‑as‑code approaches.
• Experience building custom analytical applications.