Work Location: On-site (5 days/week)
Contract Duration: 12 Months
Employment Type: Full-time Contract
Role Overview
Our Fortune 500 client is seeking a versatile Senior Backend & Data Engineer for a 12-month on-site contract to design, scale, and maintain cloud-native microservices and data pipelines. In this role, you will bridge the gap between backend services and data platforms—building reliable APIs, processing event streams, and optimizing data flow between operational and analytical systems.
Key Responsibilities
- Backend & API Development: Design, develop, and maintain backend services, APIs, and microservices in cloud-native environments.
- Data Layer Integration: Build and optimize data ingestion, transformation, and serving layers integrated directly with backend systems.
- Platform Collaboration: Partner with data engineering and platform teams to ensure seamless data flow across operational and analytical systems.
- Event-Driven Architecture: Implement scalable event-driven architectures using Kafka, SNS/SQS, or Pub/Sub.
- Service Reliability: Own end-to-end service reliability, including monitoring, alerting, defining SLOs, and handling incident response.
- Code Quality & Testing: Write clean, testable, and well‑documented code supported by comprehensive unit and integration tests.
- Technical Leadership: Participate in code reviews, architectural discussions, and technical planning.
- DevOps & Infrastructure: Contribute to CI/CD pipeline improvements and Infrastructure-as-Code (IaC) practices.
Required Qualifications
- 5+ years of professional backend development experience in Java, Kotlin, Python, Go, or a similar language.
- 2+ years of hands‑on data engineering experience building ETL/ELT pipelines, working with data warehouses, or designing data models.
- Databases: Strong proficiency with relational databases (PostgreSQL, MySQL) and NoSQL stores (DynamoDB, Redis, MongoDB).
- Cloud & Containers: Proven experience with cloud platforms (GCP and Azure preferred) and containerization tools (Docker, Kubernetes).
- System Design: Solid understanding of distributed systems, data consistency patterns, and fault‑tolerant architecture.
- Data Processing: Advanced SQL skills (window functions, CTEs, query optimization) and familiarity with data frameworks like Spark, Flink, dbt, or Airflow.
Preferred Qualifications
- Experience with streaming platforms (Kafka, Pub/Sub) and data lake architectures (Iceberg, Delta Lake, Hudi).
- Strong background in Domain‑Driven Design (DDD) and event sourcing patterns.
- Experience designing mobile‑optimized APIs (payload minimization, efficient pagination, offline‑sync patterns) and integration with push notification services (FCM, APNs).
- Knowledge of gRPC/Protobuf for high‑performance inter‑service communication.
- Hands‑on experience with IaC tools such as Terraform, AWS CDK, or Pulumi.