Jobs → Data & Analytics → Data Engineer

About the Role We are looking for a Data Engineer with strong expertise in Customer Data Platforms (CDP), Google Cloud Platform, Cloud Spanner, and real-time data engineering to build scalable pipelines supporting 100M+ customer profiles, low-latency APIs, and AI-powered customer experiences. Key Responsibilities • Build real-time and near-real-time pipelines using Pub/Sub, Dataflow, and Apache Beam • Ingest and process customer, clickstream, care, store, and network data into Cloud Spanner and BigQuery • Optimize Cloud Spanner schema, primary keys, indexes, batching, and hotspot handling for low-latency reads • Develop reusable CDC, SCD Type 2, and late-arriving-data processing patterns • Migrate and modernize existing Azure data pipelines to GCP, leveraging Databricks, Snowflake, and Azure Data Factory • Build data feeds for Customer 360, knowledge graphs, GraphQL APIs, and MCP servers supporting AI agents • Implement data quality, lineage, reconciliation, security, monitoring, and SLOs • Use Terraform and CI/CD to deploy and manage cloud-native data services • Collaborate with product, analytics, and AI/ML teams while mentoring junior engineers Requirements • 15+ years of Data Engineering experience • FAANG background mandatory • 3+ years of production experience with GCP data platforms • 3+ years of real-time / near-real-time streaming pipelines • 3+ years of BigQuery • 1+ year of Cloud Spanner • 4+ years of data modeling, ETL/ELT, SQL, and Python • 3+ years of Databricks, Spark, and Delta Lake • 2+ years of Azure and Snowflake • Hands-on experience with Pub/Sub, Dataflow, Apache Beam, and Kafka • Strong PySpark, CDC, SCD Type 2, and clickstream ingestion • Experience with Terraform, CI/CD, orchestration, and data quality