Job Description: Sr. Manager, Data Engineering RealTime CDP

Position Summary:

We are seeking a Sr. Manager, Data Engineering to lead the engineering strategy and delivery for our RealTime Customer Data Platform (CDP) with a primary focus on audience building and segmentation. You will own low latency ingestion, identity resolution, audience/segment services, latency ingestion, identity resolution, audience/segment services, consent targeting frameworks, and aware targeting frameworks, and high-performance activation APIs that power omnichannel experiences, loyalty, and marketing operations at global channel experiences, loyalty, and marketing operations at global scale.

Primary Responsibilities:

- RealTime CDP & Streaming
- Audience Building & Segmentation
- Customer Data Products & Quality
- Leadership & Delivery
- Cross Functional Collaboration

Who Were Looking For:

A Handson, strategic Data Engineering leader who can elevate real-time customer data and audience/segmentation capabilities, scale them globally, and develop worldclass engineering teams that deliver privacy safe, high-performance activation.

- Architect and scale real-time pipelines for clickstream, transactional, and behavioral data using Kafka, Flink, Spark Structured Streaming, or Dataflow/Beam.
- Design and evolve customer event models, session-inaction, and cross channel stitching to maintain a unified, channel stitching to maintain a unified, privacy aware customer view.
- Implement low latency activation APIs used by apps, web, CRM, loyalty, kiosks, and marketing orchestration platforms.
- Establish standards for observability, SLAs/SLOs, schema evolution, lineage, and cost efficiency across streaming and batch paths.




- Lead the design and operation of a scalable audience/segmentation platform supporting both real-time and batch segment creation and refresh.
- Build dynamic audience services for behavioral and lifecycle cohorts, rules driven propensity groupings, and event triggered Realtime time segments.
- Define data contracts and versioning for attributes, traits, and segment definitions to ensure reuse, durability, and protected change management.
- Set audience governance standards (freshness SLAs, recency/frequency windows, cardinality limits, consent gates) and ensure theyre consistently enforced.
- Partner with Mar Tech and Product to templatize audience playbooks (e.g., reactivation, onboarding, churn risk, high value, cartabandon).
- Own high-fidelity customer data products (profiles, attributes, segments, preferences, consent) backed by clear SLOs and documentation.
- Implement comprehensive data quality, validation, and lineage across all audience and profile pipelines.
- Create reference patterns and templates so global markets and channels can integrate quickly and safely.
- Lead, mentor, and grow global data engineering teams focused on streaming, segmentation, activation, and data product engineering.
- Drive multisugar roadmaps, manage dependencies, and deliver against business outcomes with explicit KPIs and executive reporting.
- Champion engineering excellence: testing, automation, code quality, observability, and operational readiness.
- Collaborate with Product, Mar Tech, Loyalty, Architecture, Data Governance, Security, Legal,



and Compliance to align roadmaps and ensure privacy-by design and security- by default.
- Translate marketing and product activation needs into reusable audience capabilities and APIs.
- SQL Very Strong proficiency in native SQL, has used Big Query or Athena Advanced performance tuning on large datasets.
- Languages: Python (primary), JavaScript, Node.js plus Java.
- Streaming & Processing: Kafka, Flink, Spark / Pyspark, Dataflow/Beam.
- Audience/Segmentation: Handson experience building audience engines, cohort generation logic, and audience APIs for activation.
- Data Platforms: GCP, Databricks; Big Data ecosystems (Hadoop, Lakehouse patterns); NoSQL; columnar formats (Parquet).
- Cloud: GCP preferred (Pub/Sub, Big Query, Dataflow, Cloud Run); AWS/Azure acceptable.
- Pipelines & Orchestration: ETL/ELT, Airflow/Luigi, CI/CD for data.
- Data Management: Metadata management, schema evolution, data contracts, lineage.
- Governance & Reliability: Observability, SLAs/SLOs, validation, consent/privacy controls.
- 1015 years in largescale Data Engineering / Distributed Systems.
- 5+ years leading engineering teams/squads.
- 4+ years with GCP or AWS (GCP preferred).
- 3+ years working on real time customer data and/or segmentation platforms.
- Experience with CDPs (mParticle, Adobe RTCDP, Braze, Tealium).
- Designing Realtime audience builders, rule engines, and activation frameworks.
- Multiregional deployments, data residency, and consent management at global scale.
- Strong stakeholder communication; ability to simplify technical concepts for marketers and product leaders.
- Systems thinker with strong architectural judgment and influence.

Work location: Hyderabad, India

Work pattern: Full time role.

Work mode: Hybrid.

📌 Sr Manager, Data Engineering (Hyderabad)
🏢 McDonalds in India
📍 Hyderabad