Senior/Staff Data Engineer

About the Role

We are seeking a
Senior Data Engineer
to build and stabilize the next generation of
Cake Digital Bank's unified data infrastructure
— powering analytics, dashboards, and real-time intelligence across the organization.

You will work across
streaming, batch, and lakehouse layers
, ensuring that our data pipelines and platforms —
BigQuery, Doris, and Iceberg
— operate with reliability, observability, and cost-efficiency.

This role is central to the evolution of Cake's
data mesh and lakehouse architecture
, where dashboards, dbt transformations, and machine-learning features all depend on a stable, scalable, and auditable data foundation.

Key Responsibilities

1. Data Infrastructure Stability & Reliability

• Design, implement, and maintain
  high-availability data pipelines
  that replicate data from OLTP systems to analytical warehouses (BigQuery, Doris)
• Build resilience and recovery patterns — checkpointing, replay queues, schema-aware ingestion, deduplication, and versioned storage.
• Lead
  incident response, RCA, and SLA management
  for data infrastructure components.
• Implement
  end-to-end observability
  across ingestion, transformation, and serving layers .

2. Unified Storage & Lakehouse Evolution

• Architect and operationalize
  Apache Iceberg
  as the central data storage layer to unify data across BigQuery and Doris.
• Define data layout, partitioning, compaction, and schema evolution strategy for Iceberg tables stored on
  GCS
  .
• Design
  cross-system metadata synchronization
  between Iceberg catalog, BigQuery external tables, and Doris engines.

3. Platform Automation & Scalability

• Develop and maintain
  infrastructure-as-code (Terraform, Helm, Config Sync)
  for Airflow, Flink, Doris, and BigQuery resources.
• Build self-service templates for creating new pipelines, enabling consistent deployment and monitoring.
• Optimize data infrastructure configurations to support workload growth while controlling costs.
• Automate schema detection, dependency validation, and backfill workflows for safe and predictable releases.

4. Data Governance, Quality & Security

• Integrate with
  DataHub
  to maintain end-to-end lineage, glossary, and policy-tag enforcement.
• Apply column-level security and row-level policies for
  sensitive and restricted data (PII, PCI, financial metrics)
  in BigQuery and Doris.
• Establish
  validation checks and data contracts
  to ensure quality and consistency across streaming and batch paths.
• Collaborate with Compliance and Risk teams to maintain auditable data flow and access traceability.

5. Performance Optimization & Cost Efficiency

• Continuously tune
  BigQuery slot usage, query design, and reservation policies
  by domain.
• Improve
  Doris query performance
  through partition pruning, tablet balancing, and index tuning.
• Design caching, pre-aggregation, and materialized-view strategies to accelerate dashboards while reducing query cost.
• Track job efficiency, data duplication, and storage growth across the platform.

6. Collaboration & Leadership

• Partner with BI, Risk, and ML teams to deliver reliable, low-latency data products that power business decisions.
• Mentor junior engineers on best practices for streaming systems, Airflow orchestration, and infra automation.
• Participate in architecture design sessions to guide the evolution of Cake's
  multi-engine, unified lakehouse platform
  .

Required Skills & Experience

• 5+ years
  of hands-on experience in
  data engineering or data platform development
  in a cloud-native environment
• Strong proficiency in
  SQL
  (BigQuery, Doris, or equivalent MPP engines) and
  Python
  for building, monitoring, and automating data pipelines.
• Proven experience operating
  streaming and CDC systems
  such as
  Dataflow, Flink, Debezium, or Datastream
  , with solid understanding of checkpointing, offset management, and backpressure handling.
• Deep understanding of
  data modeling and warehouse optimization
  — partitioning, clustering, materialized views, caching, and query tuning.
• Hands-on experience implementing and maintaining
  infrastructure-as-code
  using
  Terraform, Helm, or Config Sync
  .
• Familiarity with
  Apache Iceberg (or Delta/Hudi)
  and
  lakehouse design patterns
  , including schema evolution and compaction.
• Strong background in
  observability and reliability engineering
  — building dashboards, alerts, and auto-remediation for data pipelines using
  Prometheus, Grafana, or Cloud Monitoring
  .
• Understanding of
  data governance and security
  concepts: column-level security, policy tags, lineage, and data classification using
  DataHub
  or similar systems.
• Working knowledge of
  orchestration and workflow automation tools
  such as
  Airflow
  or
  Dagster
  .

Our benefits:

• Competitive compensation including a 13th-month wage and up to 3 months of performance-based bonus.
• Macbook and essential equipment are provided.
• BE Corp budget (vary from your level) is allocated for using services such as transportation, food, and passenger car bookings in Be application.
• Annual health checks and premium medical healthcare (PTI) after probation.
• 15 days of annual leave is applied for the entire employees.
• Company trips, team-building activities, and happy hour events are organized on a quarterly or annual basis.