Senior Data Engineer

Multi National Company · India

Job Title: Senior Data Engineer – Customer Data Platform (CDP)

About the Role

We are looking for an experienced Senior Data Engineer – Customer Data Platform (CDP) to design, build, and operate an enterprise-scale Customer Data Platform that unifies customer data from multiple source systems into a centralized Customer 360 platform. You will develop scalable data pipelines, implement identity resolution, build real-time data processing solutions, and enable customer insights for CRM, Marketing, Analytics, AI/ML, Contact Center, Campaign Management, and other enterprise applications.

Key Responsibilities

· Design and build scalable Customer Data Platform solutions.

· Develop ETL/ELT, CDC, and real-time streaming pipelines.

· Build and maintain Customer 360 profiles, golden records, and identity resolution capabilities.

· Develop data models, customer segmentation, and profile enrichment pipelines.

· Integrate customer data with downstream applications through APIs, event streaming, and Reverse ETL.

· Ensure data quality, governance, security, and compliance.

· Optimize data pipelines, monitor platform performance, and troubleshoot production issues.

· Collaborate with Product, Marketing, AI/ML, Analytics, and Engineering teams to deliver scalable customer data solutions.

· Mentor junior engineers and contribute to architecture and engineering best practices.

Required Skills & Experience

· 6+ years of experience in Data Engineering with at least 3 years in Customer Data Platforms (CDP), Master Data Management (MDM), or Customer 360 solutions.

· Strong expertise in SQL, Python and/or Scala, Apache Spark/PySpark.

· Hands-on experience with cloud data platforms such as Databricks, Snowflake, BigQuery, or Redshift.

· Experience with real-time streaming technologies (Kafka, Kinesis, or Pub/Sub).

· Strong knowledge of ETL/ELT, CDC, data modeling, SCD, and data warehousing.

· Experience implementing customer identity resolution and Customer 360 solutions.

· Hands-on experience with Neo4j or other graph databases.

· Experience with AWS, Azure, or GCP.

· Familiarity with Reverse ETL, REST APIs, and event-driven architectures.

Preferred Skills

· Experience with Delta Lake, Apache Iceberg, or Apache Hudi.

· Knowledge of data governance, privacy, and consent management.

· Experience supporting AI/ML and analytics data platforms.

· Exposure to enterprise-scale customer data platforms handling high-volume data processing.

Technology Stack

Languages: SQL, Python, Scala

Data Processing: Apache Spark, PySpark

Graph Database: Neo4j

Data Platforms: Databricks, Snowflake, BigQuery, Redshift

Streaming: Kafka, Kinesis, Pub/Sub

CDC: Debezium, Fivetran

Cloud: AWS, Azure, GCP

Data Lake: S3, ADLS, GCS, Delta Lake, Iceberg, Hudi

Integration: REST APIs, Reverse ETL, Webhooks