About
is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. We believe that oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise; not intuition. We are looking for team-oriented individuals with an authentic passion for accurate and predictive real-time data who can execute in a fast-paced, creative, and continually-evolving environment without sacrificing technical excellence. Our challenges are unique, so we hope you are comfortable in uncharted territory and passionate about building systems to support products across a variety of industries and consumer/enterprise clients.
Role Overview The Swish Analytics team is seeking a Senior Database Engineer to have a direct impact on the data infrastructure of our core consumer and enterprise data offerings. We’re a team passionate about accurate predictions and real-time data, and hope you find satisfaction in building new products with the latest and greatest technologies.
This is a remote position.
Responsibilities
Proficiency in Python : Writing scalable, efficient, and testable code using Python for data processing, automation, and building back-end components. Familiarity with popular Python libraries is a plus.
Cloud Platforms : Proficiency in cloud services such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, including knowledge of their specific data tools (e.g., Redshift, S3, Azure Data Factory, BigQuery).
24/7 monitoring, alerting, and incident response of enterprise database architecture.
Developing KPI's, SLA’s, SLO’s and strategy to achieve and improve database stability
Backup/recovery testing and disaster recovery planning
Developing performance testing strategy
Query performance analysis and optimization
Implement and maintain RDS Proxy and connection management strategies
Manage database environments from production, data streams, to "Big Data" analytics.
Create and maintain policy runbooks and documentation for company use.
Database security, access control, and compliance
Working with MySQL/Postgres, Redshift, Kafka, Athena, Redis/Valkey, S3 and similar
Own schema migration tooling and process development
Skills Guide
Operational Excellence : Monitoring (CloudWatch, Performance Insights, Datadog), alerting, on-call experience
MySQL Operations : Deep knowledge of RDS operational functions, performance tuning (indexes, query optimization, explain plans); backup/restore, point-in-time recovery, replication troubleshooting
SQL Mastery : Proficiently writing and understanding complex SQL queries, including joins, subqueries, aggregations, and window functions.
Database Design Principles : Knowledge of normalization, denormalization, and how table structure impacts query performance.
Indexing : Understanding different index types (B-tree, hash, clustered, non-clustered) and their appropriate use for optimizing search and retrieval.
Automation : Software development for operational tasks
AWS : RDS operations, Authentication, Authorization
Incident Management : Root cause analysis, postmortem creation, Run book development
Nice to Have
Performance testing tools
(sysbench, HammerDB)
Execution Plan Analysis : Ability to read and interpret query execution plans to identify bottlenecks, such as full table scans, inefficient joins, or missing indexes.
Identifying Resource Bottlenecks : Pinpointing where queries are consuming excessive CPU, I/O, connections, or memory.
Base salary:
Starting at $145,000 base
Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law. The position responsibilities are not limited to the responsibilities outlined above and are subject to change. At the employer’s discretion, this position may require successful completion of background and reference checks.
Department Data Engineering
Locations San Francisco, CA - Remote
Remote status Fully Remote
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Languages
- English
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