Data Engineer

Data Engineer Identity Resolution & Consent Data (IC TR-5)

Location: Bangalore or Hyderabad

Department: D&A

We are seeking a Data Engineer Identity Resolution & Consent Data to join our Privacy Technology team. This role will own the data infrastructure that determines who T knows a person to be and what they've consented to not the consent collection, but the identity resolution and data modeling layer underneath them.

In this role, you'll spend your days designing and maintaining the pipeline that matches and unifies customer and contact records across CRM, marketing automation, and other source systems into a single enterprise identity; modeling consent data from our Consent Management Platform (OneTrust) so it can be reliably tied to that identity; and applying AI tools to automate the data quality review and categorization work that keeps the pipeline accurate as new sources and volume are added. You will be the technical authority on how identity and consent data are structured and connected at TR, translating privacy and business requirements into accurate, scalable data models.

Key Responsibilities

• Own the design, configuration, and governance of TR's identity resolution pipeline — the matching, scoring, and clustering logic that unifies customer and contact records from CRM, marketing automation, and other source systems into a single enterprise identity.
• Define and enforce standards for onboarding new source systems into identity resolution, including data quality tiering, matching keys, and incremental processing, as new business units and data sources come online.
• Translate jurisdictional consent requirements into accurate data models — consent purpose definitions, per-individual consent state, and receipt-to-purpose mapping — sourced from the enterprise Consent Management Platform.
• Partner with Privacy, Legal, and Marketing to ensure that identity and consent data models correctly reflect jurisdictional requirements and support downstream marketing, subject-request, and reporting use cases.
• Own the consent signal chain from CMP ingestion through to the resolved identity layer — validating that consent and preference signals are correctly anchored to the right individual, and flagging cases where source systems disagree rather than silently picking a winner.
• Maintain and evolve the matching and clustering logic that powers identity resolution, ensuring it scales incrementally as new data and sources arrive without reprocessing stable relationships.
• Apply AI tools to automate data quality review, match validation, and field mastering across the identity and consent data pipeline, proactively identifying opportunities to reduce manual review effort.
• Own field-mastering logic for cases where multiple source systems report conflicting values for the same individual, keeping outputs aligned to documented business rules as requirements evolve.
• Build and maintain the engineering tooling, testing, and monitoring that keep the identity and consent data pipeline reliable, auditable, and cost-efficient.
• Support go-live validation for new source onboarding and consent or identity model changes, confirming data quality before promotion to production.

Qualifications

Required:

• 5-7 years of experience in data engineering, privacy engineering, or identity resolution.
• Hands-on experience with SQL and a cloud data warehouse (Snowflake or similar).
• Hands-on experience with dbt (or a comparable SQL-based transformation framework), including incremental model design and materialization strategies.
• Proficiency in Python for pipeline tooling, automation, and testing.
• Working knowledge of GDPR, CCPA/CPRA, CASL, and other global frameworks governing consent and marketing communications, applied at the data modeling layer.
• Understanding of identity or entity resolution concepts — matching, scoring, and clustering records into a single identity.
• Hands-on experience integrating Consent Management Platform data (OneTrust or similar) into downstream data systems.
• Familiarity with how consent and identity signals integrate with CRM and marketing technology stacks.
• Strong attention to detail with the ability to manage data quality across a large, multi-source data estate.
• Demonstrated use of AI tools (Microsoft Copilot, Claude Code, or Python-based LLM workflows) to automate data quality, categorization, or review tasks.

Preferred:

• Experience designing or operating identity resolution or entity resolution pipelines at scale.
• Familiarity with marketing technology platforms (Salesforce, Eloqua, or similar) and how consent and identity data are consumed downstream.
• Familiarity with pipeline orchestration tools (e.g., Airflow) for scheduling production data pipeline runs.
• Familiarity with procedural scripting extensions (e.g., JavaScript stored procedures) for logic not easily expressed in declarative SQL.
• Familiarity with cloud-based export/import workflows for identity or consent data (e.g., AWS).
• Experience in a B2B enterprise software environment with a complex, multi-system data landscape.