Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

The Business Intelligence Engineer manages enterprise data sources, supports data quality and governance, and translates transactional data into KPIs for business teams. Responsibilities include guiding analyst teams, handling data inquiries, supporting advanced analytics, monitoring data performance, defining data requirements with stakeholders, and presenting findings to technical and non-technical audiences. The role requires SQL, Tableau, relational database, and data modeling or analytics expertise.

Designs, administers, and improves highly available PostgreSQL database platforms across AWS and GCP. Responsibilities include database architecture, performance tuning, replication, backups, disaster recovery, production incident response, Kubernetes operations, infrastructure as code with Terraform, and GitOps automation. The role also supports Kafka, ETL, CDC, monitoring, compliance audits, and resilient cloud-native database deployments.

Design, scale, and maintain high-performance services supporting player registration, authentication, identity verification, fraud and AML screening, geolocation, responsible gaming, regulatory compliance, and communications. The role involves architecting features, optimizing production systems, managing monitoring and integrations, mentoring engineers, handling migrations, and collaborating across teams. Candidates will operate containerized services, support on-call rotations, and build secure, auditable systems using modern web frameworks, databases, event infrastructure, and authentication standards.

Build and optimize data transformation pipelines using SQL, dbt, Airflow, Python, BigQuery, and relational databases. Collaborate with stakeholders and data engineers, manage task scheduling, resolve data issues, perform analyses, present recommendations, support data exploration tool adoption, and mentor team members. The role also contributes to hiring, onboarding, and professional development while ensuring data accuracy and insight quality.

Drive enterprise automation initiatives from opportunity identification through delivery and optimization. Partner with business leaders, engineering, data, security, product teams, RPA specialists, AI strategists, and vendors to prioritize and implement scalable solutions. Manage the automation portfolio, vendor relationships, discovery and intake processes, delivery alignment, and performance metrics. Evaluate AI-supported process improvements, ensure compliance and operational readiness, and deliver measurable gains in efficiency, quality, cycle time, and stakeholder satisfaction.

Supports 24/7 sports betting operations by assisting traders, monitoring pre-game and in-play markets, reviewing betting content, testing app functionality, managing sport and competition setups, conducting compliance checks, communicating with data providers, and escalating operational issues. The role also supports customer issue resolution and cross-functional assignments with Compliance, Marketing, and Product. Evening, weekend, and holiday availability is required.

Design, scale, and optimize APIs, services, databases, and critical wagering, financial ledger, and regulatory systems. Lead complex technical initiatives, improve production performance and resilience, build integrations and migrations, manage monitoring, and mentor engineers. The role requires ownership of end-to-end delivery, on-call operations, scalable distributed systems, GraphQL, relational databases, Kubernetes, asynchronous processing, and highly accurate, auditable financial systems.

Leads the design and delivery of scalable data pipelines, dbt models, orchestration workflows, and analytical data models. Establishes data architecture, engineering standards, quality frameworks, governance, observability, and self-service analytics practices. Partners with stakeholders, leads technical reviews, mentors engineers, supports hiring, oversees analyses, and participates in incident response and continuous improvement.

Design, build, and scale GraphQL and gRPC APIs and SQL queries powering the sportsbook marketplace. Own end-to-end feature delivery, performance diagnostics and remediation, release and deployment windows, monitoring in DataDog, and on-call rotations. Mentor peers, draft technical proposals/specs, and improve platform scalability through load testing, tracing, and production hygiene.

Lead design and delivery of platform capabilities that power a Federated GraphQL API and event-driven systems. Build and optimize gRPC endpoints, GraphQL APIs, and SQL for scale; own observability (DataDog, Bugsnag), mentor engineers, drive integrations, improve performance and reliability, and support customer-facing product teams across the organization.