Top Tech Jobs & Startup Jobs

Lead production support and continuous improvement for an Azure and Databricks data platform. Responsibilities include incident resolution, root-cause analysis, stakeholder communication, monitoring, performance and cost optimization, data quality and governance, change and release management, KPI reporting, documentation, training, and automation including self-healing capabilities.

Design and build Go-based integration services, APIs, and event-driven workflows using AWS SQS, SNS, Lambda, EKS, Kubernetes, and RDS. Develop resilient, observable, well-tested services with strong API contracts, schema evolution, and enterprise integration patterns. Contribute to containerization, CI/CD, performance tuning, and non-functional validation. Use AI-assisted development responsibly, review code, mentor developers, and provide technical guidance.

Designs and maintains scalable data pipelines, develops dbt transformation workflows, and architects Snowflake data models and warehousing solutions. Integrates multiple data sources, implements quality monitoring, troubleshoots pipeline issues, optimizes SQL and warehouse performance, documents architecture, and collaborates with analysts, data scientists, and stakeholders to deliver reliable analytics infrastructure.

Designs, develops, and optimizes Snowflake and dbt data warehouses, ELT/ETL pipelines, dimensional models, and data quality frameworks. Builds reusable dbt models, tests, snapshots, documentation, and CI/CD workflows. Ensures data governance, security, compliance, metadata management, and lineage while troubleshooting data issues. Collaborates with analysts, data scientists, product teams, and stakeholders, documents architectures, and mentors junior engineers.

Build and evaluate predictive models for complex transactional data, using advanced SQL, Python, cloud data infrastructure, and statistical methods. Trace data quality issues through ETL and CDC pipelines, communicate findings to senior leaders and nontechnical stakeholders, and use AI tools to accelerate analysis. Preferred work includes LLM, RAG, BI, data testing, vector database, and commercial real estate applications.

Leads discovery, architecture, prototyping, and delivery enablement for AI-powered business solutions. Designs generative AI, agentic, RAG, automation, predictive, and hybrid systems; guides developers through implementation; evaluates platforms and models; and embeds responsible AI, security, privacy, governance, observability, and evaluation controls. The role also creates reusable architectures and playbooks, communicates technical decisions to executives and stakeholders, and mentors engineers through architecture and code reviews.

Own the customer-facing React and TypeScript metrics platform, including dashboards, tables, filters, charts, saved views, routing, state, API validation, and performance. Extend FastAPI endpoints, write migrations, review backend code, support production issues, and deliver features end to end across the stack. Maintain quality through testing, accessibility, responsive design, and scalable data visualization.

Lead discovery, architecture, prototyping, and delivery enablement for AI-powered business solutions, including generative AI, agentic systems, RAG, automation, predictive models, and data integration. Design secure, observable, governed architectures; evaluate platforms and models; build proofs of concept; guide developers through implementation; communicate decisions to technical and executive stakeholders; and create reusable architecture and responsible AI assets.

Lead enterprise cloud platform strategy, architecture, engineering, and operations. Build secure, scalable, cost-effective cloud, Kubernetes, automation, developer platform, and AI capabilities. Establish governance, security, observability, reliability, disaster recovery, FinOps, and SRE practices. Lead cloud, platform, DevOps, and SRE teams while partnering with application, security, data, and product stakeholders and communicating investment priorities to senior leadership.

Leads enterprise data and integration architecture, including platform-to-MDM and platform-to-application integrations. Owns solution architecture from requirements through operational support, establishes data governance and architectural standards, designs scalable data warehouses, and guides cross-functional teams. The role also provides technical leadership, conducts architecture reviews, ensures security and performance alignment, resolves complex integration challenges, and influences enterprise-wide technology decisions.