Site Reliability Engineering (SRE) (Trading, Exchange - Salary Package Upto 1M+)

Salary: $55,000 – $65,000 per month

About the Role

We are looking for a Senior SRE & Data Platform Engineer to own the reliability, observability, and data integrity of our high-throughput, near-real-time streaming infrastructure. In this role, you will bridge the gap between core infrastructure, data engineering, and system reliability. You won't just monitor a platform—you will design the end-to-end telemetry strategy, build robust real-time data pipelines, and ensure that billion-row queries return in milliseconds.

This is a critical position within a low-latency, event-driven ecosystem where an engineering decision directly impacts platform performance and data accuracy.

Core Responsibilities

SRE & Observability (Primary Focus)

• End-to-End Telemetry Ownership: Design, instrument, collect, store, and visualize platform telemetry. Decide exactly what metrics matter to drive business and engineering decisions.

• Context-Driven Alerting: Architect Grafana dashboards and intelligent alert systems that isolate root causes and prescribe remediation steps, moving beyond simple static threshold alerts.

• Production Operations: Proactively diagnose silent system failures, execute data recovery for missed streams, and engineer permanent fixes to prevent incident recurrence.

• GitOps & Deployment: Own the CI/CD lifecycle, ensuring safe software delivery with a deep operational understanding of the path from "code merged" to "system live."

• Kubernetes Infrastructure: Manage and scale streaming workloads on AWS (EKS), handling resource budgeting, configuration delivery, and capacity planning.

• Infrastructure as Code (IaC): Maintain and provision the underlying AWS infrastructure using production-grade Terraform configurations.

• On-Call Support: Participate in an on-call rotation dedicated to safeguarding our core data and observability platform.

Data Pipeline Engineering

• Real-Time Streaming: Build and maintain high-availability, near-real-time ingestion pipelines handling mission-critical telemetry and trading logs.

• Data Guarantee Reasoning: Evaluate and implement delivery guarantees (at-most-once vs. at-least-once) and manage their downstream impact on analytics accuracy.

• Data Quality & Governance: Design robust data validation checks that isolate and route anomalous records to quarantine/DLQ targets rather than dropping them silently.

• OLAP Architecture: Design, tune, and optimize columnar tables to guarantee sub-second execution speeds on billion-row datasets using smart partitioning, sort keys, and deduplication.

• Analytical Engineering: Author and optimize high-performance SQL to power backend data layers, dashboards, and complex business logic (e.g., executing changes like computing p99 latency per trading venue).

What We Are Looking For

• Education: Degree in Computer Science, Software Engineering, or equivalent production experience.

• Production Observability: Extensive experience troubleshooting live incidents using a modern observability stack (e.g., Prometheus, Grafana, Loki, ELK, Datadog, or CloudWatch).

• Stream Processing: Practical experience operating distributed stream processing engines at scale (e.g., Apache Flink, Spark Structured Streaming).

• OLAP Expert: Deep knowledge of columnar databases, including advanced table design and query tuning (e.g., ClickHouse, BigQuery, Druid, Redshift).

• Container Orchestration: Solid working knowledge of Kubernetes internals (deployments, pod lifecycles, configuration injection, and resource limits).

• Programming & SQL: Strong proficiency in at least one backend language (Python, Java, Scala, or Rust) paired with exceptional, fluent analytical SQL.

• Event-Driven Architectures: Familiarity with high-throughput message brokers and queues (e.g., Kafka, AWS SQS).

• Systems Mindset: A methodical approach to debugging distributed systems, and a strong engineering instinct to fix systemic root causes rather than symptoms.

Nice to Have

• Production experience with OpenTelemetry (OTel), distributed tracing, and navigating high-cardinality telemetry pipelines.

• Workflow orchestration and DAG scheduling expertise using Apache Airflow.

• Advanced Infrastructure as Code execution, including writing reusable Terraform modules, managing state drift, and performing targeted applies.

• Familiarity with multi-module project compilation and modern build tools (Gradle, sbt, Maven, or Cargo).

• Prior exposure to algorithmic trading environments, market data delivery, or other ultra-low-latency financial engineering domains.