Swish Analytics

Swish Analytics is an online sports betting and fantasy sports platform aimed at enhancing the accuracy and efficiency of sports analytics. The platform promotes an environment of

Senior Data Platform Engineer

Location

California

Posted

12 days ago

Salary

$0 - $180K / year

Seniority

Senior

Job Description

Senior Data Platform Engineer

Swish Analytics

Title: Senior Data Platform Engineer Location: San Francisco, United States - Remote, United States This is a remote position. Job Description: In order to be considered for this role, after clicking "Apply Now" above and being redirected, you must fully complete the application process on the follow-up screen. Company Overview Swish Analytics 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're 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 Data Platform 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. Seniority: Solid Senior level (5-8 years experience) Core Responsibilities: - Proficiency in Python: Expertise in 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 $180,000+ - DOE 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.

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