Top Tech Jobs & Startup Jobs

Designs and deploys production AI solutions and data platforms, leads architecture and implementation discussions, presents technical solutions to customers and executives, evaluates AI trade-offs, and identifies revenue-growth opportunities within existing accounts.

Administer, monitor, and maintain the enterprise Snowflake environment, including access controls, resource monitors, warehouses, and account settings. Troubleshoot technical, performance, and access issues across teams; evaluate new Snowflake capabilities; and promote best practices for query performance, cost management, and governance. Document platform standards and operational procedures while collaborating with data engineering, analytics, and platform teams.

Own production support for SnapLogic and dbt data integration pipelines, including monitoring, incident response, ticket triage, root-cause analysis, SLA adherence, and performance optimization. Lead and mentor a small support team, manage on-call rotations, maintain runbooks, coordinate releases and change management, report operational metrics, and communicate issue status with engineering and client stakeholders.

Designs, develops, and optimizes scalable Snowflake and dbt data warehouse solutions, including ELT/ETL pipelines, dimensional models, data quality frameworks, CI/CD workflows, governance, and lineage documentation. Collaborates with analytics and business teams, troubleshoots data issues, establishes engineering standards, and mentors junior engineers. The role also requires Azure Data Factory experience and expertise handling structured and semi-structured data.

Leads U.S. go-to-market and demand-generation strategy for enterprise technology services. Owns ABM, integrated campaigns, partner programs, executive events, industry marketing, marketing operations, funnel reporting, and pipeline attribution. Collaborates with sales, SDRs, executives, and technology partners to generate enterprise opportunities and revenue. Builds the marketing operating model, team, processes, and supporting technology while translating complex Data, AI, Cloud, Analytics, and Digital Transformation services into compelling buyer messaging.

Designs, develops, and optimizes scalable data infrastructure, ETL/ELT pipelines, distributed processing workflows, and cloud data platforms. Owns identity resolution, data integration, modeling, governance, privacy, quality, lineage, and monitoring solutions. Collaborates with data science and analytics teams, leads architectural decisions, mentors engineers, conducts code reviews, and promotes reliable, secure, cost-efficient engineering practices.

Leads development of statistical and machine learning models for marketing measurement and optimization. Owns attribution, marketing mix modeling, causal inference, incrementality analysis, experimentation, predictive modeling, and optimization solutions. Works with large-scale media and customer datasets, identity and privacy-aware analytics, and production model monitoring. Collaborates with engineering and product teams, establishes validation standards, communicates insights to stakeholders, reviews technical work, and mentors junior data scientists.

Designs and maintains scalable ETL/ELT pipelines using SQL, Python, and cloud data platforms. Integrates data from multiple sources, implements quality and monitoring controls, troubleshoots performance issues, supports data modeling for analytics and machine learning, and follows security and governance practices. Collaborates with engineers, data scientists, and stakeholders while documenting pipelines and exploring AI-assisted development tools.

Develops, validates, and maintains statistical and machine learning models for business measurement and analytics. Responsibilities include exploratory data analysis, feature engineering, causal inference, attribution modeling, data quality validation, model monitoring, privacy-aware analytics, and communicating insights to stakeholders. The role collaborates with data engineering and cross-functional teams using large, multi-source datasets and cloud data platforms.

Designs and drives enterprise architecture strategies across applications, APIs, data platforms, integrations, and cloud environments. The role develops current- and future-state architectures, technology roadmaps, data models, governance practices, ETL and data warehouse solutions, and supports digital transformation initiatives. It also provides technical guidance to engineering teams, evaluates technology options, presents architecture recommendations, and partners with business and technical stakeholders in investment management, commercial real estate, and critical infrastructure environments.