Senior Data Engineer

Tasks

• 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
• Local Candidates Only

Schedule

• Contract-to-Hire (C2H)

Location

• Atlanta, GA