Senior Backend Engineer (PostgreSQL Optimization)
Effodio, Inc.
Job Description
Effodio
\nSenior Backend Engineer (PostgreSQL Optimization)
\nFull-Time | Remote
\n \nAbout Effodio
\nFounded by industry veterans from Google, Arista, and other leading tech companies, Effodio is building a next-generation analytics platform that provides real-time insights into application and infrastructure performance.
\n \nEffodio (Latin): “I dig, excavate, or mine.”
\n \nJob Summary
\nWe are looking for someone with deep experience optimizing databases, both SQL and NoSQL, for performance and scale. Our platform ingests and analyzes high-volume time-series data. We are looking for a candidate with experience with technologies such as PostgreSQL, Timescale, Redis, and Elasticsearch. This is a hands-on backend engineering role in Go, not a DBA position. Day-to-day, you’ll be writing code and building across the platform. Your database expertise will be especially valuable as we tackle performance and scalability challenges across these data stores. Once that work is in a solid, maintainable place, you’ll contribute across other backend projects as well.
\n \nWhat You’ll Do
\nBackend Development (Primary Focus)
\n- \n
- Design, build, and ship backend services and features in Go with a GraphQL API layer \n
- Write clean, efficient, and maintainable production code across the full development lifecycle \n
- Contribute to system design, architecture, and implementation of scalable services across multiple coordinated services \n
Database Optimization (Specialty Area)
\n- \n
- Analyze and optimize PostgreSQL/TimescaleDB queries using EXPLAIN ANALYZE, identifying slow paths in time-series and relational workloads \n
- Design and implement indexing strategies (B-tree, GIN, BRIN, partial, hypertable indexes) tailored to query patterns \n
- Optimize Redis caching layers and Elasticsearch indexing/query performance \n
- Identify and resolve performance bottlenecks across the full data path - ingestion, storage, query, and retrieval \n
- Evaluate and recommend data store choices (SQL vs. NoSQL) for new features based on access patterns and scale requirements \n
Data Modeling & Schema Design
\n- \n
- Design schemas that support both performance and scalability across PostgreSQL, TimescaleDB, and Elasticsearch \n
- Implement partitioning, hypertable, and retention strategies for high-volume time-series data \n
- Balance tradeoffs between performance, maintainability, and data integrity across SQL and NoSQL stores \n
Distributed Systems & Cloud Architecture
\n- \n
- Build and operate services deployed on Kubernetes across AWS and GCP \n
- Design for reliability, fault tolerance, and high availability with proper observability (OpenTelemetry, Prometheus) \n
Performance & Scalability
\n- \n
- Optimize across the full stack: application code, database queries, caching layers, and search indexes \n
- Troubleshoot complex production issues across services, data pipelines, and data stores \n
- Use distributed tracing and metrics to identify and resolve latency and throughput bottlenecks \n
Cross-Functional Collaboration
\n- \n
- Partner with product, data, and engineering teams to deliver high-impact solutions \n
- Contribute to technical discussions and help drive pragmatic engineering decisions \n
What You Bring
\nExperience
\n- \n
- 7+ years of backend software engineering experience \n
- Strong track record of building and operating production systems at scale \n
Database Expertise (Required)
\n- \n
- Hands-on experience optimizing PostgreSQL (and ideally TimescaleDB or similar time-series extensions) in production \n
- Strong understanding of query performance, indexing strategies, and execution plans \n
- Experience with at least one NoSQL data store (Redis, Elasticsearch, or similar) in a production capacity \n
- Experience working with large datasets and high-throughput data ingestion pipelines \n
Technical Skills
\n- \n
- Proficiency in Go is highly desired; we’ll invest in training the right engineer \n
- Experience with cloud platforms (AWS and/or GCP) \n
- Familiarity with Kubernetes and containerized systems \n
- Bonus: experience with GraphQL APIs, OpenTelemetry, Kafka, or time-series databases \n
Compensation
\nIndividual compensation is determined by skills, qualifications, and experience. Compensation includes salary, equity, and a discretionary bonus.
\n \nWork Authorization
\nApplicants must have legal authorization to work in the United States. Effodio does not sponsor employment visas for this role.
\n \nEqual Opportunity Employer
\nEffodio is an Equal Opportunity Employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.
\n \nAI in Our Hiring Process
\nEffodio uses AI-enabled recruiting tools to improve efficiency and consistency in our hiring process. These tools may assist with resume review, scheduling, and communication. AI supports but never replaces human decision-making, and all hiring decisions are made by people.
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