Data Engineer with Expert-level SQL

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired bya collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizationsunlock the value of technology and build a more sustainable, more inclusive world.

Onsite : New York

Job Description

Key Responsibilities

Pipeline Engineering

Design and maintain high-throughput ingestion pipelines for transaction signals, behavioral events, and third-party identity graphs - including LiveRamp RampID, UID2, GCLID chains, and household device graphs

Implement identity resolution logic at scale: deterministic matching, probabilistic graph construction, and household + device-level cluster assembly across 1B+ data points

Build and maintain data clean room connectors and privacy-preserving data exchange pipelines (AWS Clean Rooms, LiveRamp DCR, Google ADH, or equivalent)

Develop integrations between activation platforms (email, CDP, DSP) and the identity graph layer - supporting real-time audience push and match rate monitoring

Data Modeling & Quality

Design medallion-architecture or equivalent data models optimized for cohort-level LTV/CAC attribution and multi-touch attribution across owned, paid, and clean room channels

Build automated QC and reconciliation frameworks - deduplication, compliance validation, and data lineage tracking - capable of reducing manual reconciliation cycles from weeks to hours

Implement PII governance controls at the pipeline layer: redacted ID egress, consent signal propagation, and guardrail validation aligned to GLBA, Fair Lending, UDAAP, and TCPA/CAN-SPAM

Platform Integration

Integrate LLM-based APIs (e.g., Anthropic Claude, OpenAI, Vertex AI) for AI-powered signal enrichment, audience brief generation, and compliance pre-screening within pipeline workflows

Build serverless microservices and API bridge layers connecting clean room outputs to activation destinations - using any major serverless or edge compute platform

Maintain and evolve authentication, email notification, and managed database services supporting platform-facing APIs and client-facing tooling

Required Qualifications

5+ years of data engineering experience

Expert-level SQL across at least one major cloud data warehouse: Snowflake, Google BigQuery, Amazon Redshift, or Azure Synapse

Proficiency in Python for pipeline development, transformation logic, and data quality automation

Hands-on experience with at least one clean room technology: AWS Clean Rooms, LiveRamp DCR, Google ADH, InfoSum, or equivalent privacy-preserving data collaboration platform

Deep understanding of identity resolution concepts: deterministic matching, probabilistic graph construction, household-level aggregation, and device graph assembly

Strong PII governance knowledge: data residency, consent frameworks, and financial services regulatory requirements (GLBA, Fair Lending, UDAAP)

Experience integrating with DSPs, CDPs, or marketing activation platforms at the data layer

Ability to operate in client-facing consulting delivery contexts - translating business requirements into technical specifications

Preferred Qualifications

Experience with graph database technologies - Neo4j, Amazon Neptune, or TigerGraph - for identity graph storage and traversal

Familiarity with LiveRamp Embedded Identity, UID2 token handling, or walled garden attribution integrations (Google ADH, Meta CAPI, Amazon Attribution)

Working knowledge of LLM APIs for structured data enrichment and AI-assisted pipeline workflows"

The base compensation range for this role in the posted location is: $100000 to $130000

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are