Senior Software Engineer, Cloud Applications
New
J
JobgetherCloud software
Fully remote working arrangements within the United States.Full-TimeSenior
SalaryAnnual base salary determined by geographic compensation tier: US Tier 1: $176,000 – $231,000. US Tier 2: $158,400 – $207,900. US Tier 3: $140,800 – $184,800.
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Job Details
- Required Skills
- PostgreSQLKubernetesApache KafkaClickhouseGoDistributed Systems
Requirements
- Extensive experience designing, developing, and delivering production-grade backend systems in cloud environments.
- Experience owning system architecture, reliability, and operational performance.
- Strong proficiency in at least one systems programming or backend development language; Go is preferred.
- Hands-on experience building and operating distributed systems, including concurrency, scalability, consistency, fault tolerance, and failure recovery.
- Experience designing and maintaining data pipelines and storage systems, including technologies such as PostgreSQL, Redshift, Kafka, Kinesis, S3-compatible storage, and ClickHouse.
- Understanding of cloud data storage and processing platforms such as Snowflake, Databricks, BigQuery, Google Cloud Storage, and Azure Blob Storage.
- Experience with cloud infrastructure and container orchestration, particularly Kubernetes.
- Strong understanding of data architecture, event-driven systems, schema design, data integrity, and high-throughput processing.
- Experience ensuring data correctness, quality, and traceability in production environments.
- Production operations experience with observability, monitoring, incident management, performance optimization, on-call readiness, and continuous delivery.
- Experience with the Temporal framework or similar workflow orchestration technologies is an advantage.
Responsibilities
- Lead the design, development, and delivery of business-critical cloud services.
- Own architecture for systems supporting namespace management, customer isolation, workflow operations, audit logging, and data exports.
- Design and optimize high-throughput data pipelines for usage and operational data.
- Translate business and analytical requirements into durable event schemas and data models.
- Establish data quality standards, including schema contracts, pipeline validation, anomaly detection, and alerting.
- Improve system observability, incident response, performance monitoring, and operational readiness.
- Troubleshoot production incidents, optimize performance, and prevent recurring issues.
- Conduct architecture and code reviews, document technical decisions, and introduce reusable development patterns and tools.
- Mentor engineers and collaborate with product managers, analytics, solutions architects, and other engineering teams.
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