Senior DataOps Lead – AI-Driven Data Platform Operations (Snowflake, dbt, Fivetran)

Senior DataOps Lead – AI-Driven Data Platform Operations (Snowflake, dbt, Fivetran)

Location: Irvine, CA – Onsite at End Client Location

Employment Type: Contract-to-Hire (C2H)

W2 Pay Rate: $60-70/hour, depending on experience. Anticipated FTE Conversion Salary: Approximately $140,000 annually

Contract Duration: Approximately 3–6 months, with the goal of full-time conversion

Conversion Requirement: Must be willing and eligible to convert to full-time employment.

C2C Eligibility: No third-party staffing or consulting firm candidates. Independent consultants operating through their own corporation or LLC are welcome, subject to applicable insurance, compliance, and contractual requirements. All candidates must be willing to convert to full-time employment.

KORE1 , a nationwide provider of staffing and recruiting solutions, has an immediate opening for a Senior Forward-Deployed DataOps Lead – AI & Modern Data Platforms .

About the Opportunity

Our client is a growing, global AI and digital transformation professional services firm that helps organizations turn business strategies into practical digital, data, and AI solutions. The firm partners with enterprise clients across multiple industries to improve operations, accelerate modernization, enhance customer experiences, and deliver actionable insights. Its services include:

• AI Application Development
• Data, Digital, and Cloud Acceleration Using AI
• AI-Native Product Engineering

This position will be embedded directly onsite with one of the firm's enterprise clients in Irvine, CA , working closely with the client's IT leadership, business stakeholders, and data engineering teams.

The Role

We are looking for an AI-native Senior Forward-Deployed DataOps Lead to own the end-to-end health of an enterprise client's data environment, serving as the single accountable control tower across a hybrid data platform.

What distinguishes this role is how you get there: you will help build a service that detects, correlates, and increasingly resolves issues autonomously, applying AIOps, GenAI, and agentic automation to accelerate triage, predict failures, and convert repetitive manual intervention into automation—while maintaining human oversight at critical decision points.

The role requires technical and client engagement leadership in equal measure. You will be the face of the service to client IT and business leadership, run the governance cadence, and own the delivery relationship.

This is a hands-on, forward-deployed position requiring close collaboration with the client's existing engineering team. You will not only build and operate solutions but also explain technical decisions, mentor client engineers, and ensure successful knowledge transfer and adoption.

The ideal candidate will challenge the status quo, proactively identify opportunities to improve operations, and leverage AI to increase productivity and service reliability.

What You Will Do

Engagement & Client Leadership

• Act as the primary point of accountability to client IT leadership and business data owners for the end-to-end data service across legacy and modern technology stacks.
• Chair the operational governance cadence—including daily stand-ups, weekly cross-party operations reviews, and monthly business reviews—and own the agenda, decisions, and follow-through.
• Own the service scorecard and its narrative, including SLA attainment, MTTR, data freshness, repeat-failure rates, pass rates, connector stability, and FinOps.
• Protect the scope boundary between run and change activities; route enhancement requests through governance and size and shape change requests.
• Lead client communication during major incidents and own post-incident reviews.
• Work directly alongside client data engineers, providing technical guidance, mentoring, and knowledge transfer.
• Serve as a trusted technical advisor, helping stakeholders understand proposed solutions, evaluate alternatives, and make informed decisions.
• Review new business demands, assess technical feasibility, estimate effort, and help define implementation roadmaps.

Service Ownership & Operations

• Own the Standard Operating Procedures (SOPs) for the data environment, including scope, monitoring framework, severity matrix, RACI, escalation paths, notification matrix, and closure criteria.
• Lead triage for P1 and P2 incidents, assign resolver domains, and coordinate cross-functional incident response.
• Drive problem management by converting recurring incidents into permanent fixes and reducing the problem backlog.
• Oversee production support and operational reliability across legacy and modern enterprise data platforms.
• Establish and maintain monitoring, alerting, and data-quality frameworks that measure data delivery and reliability, not just job execution.
• Coordinate incident resolution across third-party hosting providers, SaaS vendors, and internal application teams.
• Identify opportunities to reduce operational toil, improve service performance, and automate repetitive support activities.
• Monitor and evaluate deployed AI agents and automated workflows to ensure reliability, accuracy, operational value, and continued effectiveness.

Technical Leadership

• Set the technical standards for the service across legacy and modern data technology stacks.
• Provide input on data architecture and modeling standards, working collaboratively with the Data Architect responsible for dimensional modeling, conformed dimensions, business keys, slowly changing dimensions (SCD), and semantic consistency.
• Lead diagnosis of major incidents across technology domains, distinguishing ETL faults from database faults, connector issues from source schema changes, and reporting failures from warehouse contention.
• Own operational decisions and define monitoring, observability, and data-quality frameworks.
• Support and optimize modern data pipelines and workflows utilizing Snowflake, dbt, Fivetran, and related technologies.
• Support legacy data environments, including Informatica PowerCenter and Db2, during ongoing modernization and migration activities.
• Support enterprise BI operations, including MicroStrategy, with future modernization initiatives involving Power BI.
• Work with enterprise scheduling and orchestration tools, including Tidal, to monitor and troubleshoot data processing workflows.
• Establish and advance AIOps capabilities, moving the service toward predictive, intelligent, and self-healing operations.
• Help architect, build, and implement agentic AI capabilities for platform operations in collaboration with the broader engineering team.
• Apply ML and GenAI to operational use cases such as anomaly detection, log and incident clustering, LLM-assisted triage, incident summarization, and runbook generation.
• Evaluate the effectiveness of AI-driven automation, identify areas for improvement, and ensure solutions remain reliable following deployment.
• Collaborate with client engineering teams on platform modernization, including enterprise data integration and evolving ERP and analytics environments.

Requirements

What You Bring

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Strong professional experience in data engineering, data warehousing, or DataOps, including hands-on production support and operational leadership. Senior-level experience is preferred; candidates with approximately 5–6 years of highly relevant experience will also be considered.
• Demonstrated production support leadership experience, including incident management, operational ownership, troubleshooting, and service delivery.
• Experience with at least two relevant enterprise data platform technologies, particularly Snowflake, dbt, Fivetran, Informatica PowerCenter, or comparable modern and legacy data technologies.
• Knowledge or hands-on experience implementing agentic AI solutions, AI-powered automation, or intelligent platform operations.
• Demonstrated ability to architect, build, implement, or meaningfully contribute to AI agents and automated workflows, including understanding how to evaluate and monitor their effectiveness.
• Experience as a client-facing or internal service lead, including governance forums, SLA ownership, service reporting, and escalations with IT and business stakeholders.
• Strong SQL and data modeling expertise, including familiarity with dimensional modeling and warehouse performance tuning.
• Practical experience with enterprise job scheduling tools such as Tidal, Control-M, Autosys, or equivalent.
• Experience with ITSM processes and platforms such as ServiceNow, including incident, problem, change, and major incident management.
• Ability to define and operate monitoring and alerting frameworks that measure data delivery, quality, freshness, and service reliability.
• Experience with AIOps, intelligent observability, or automation in production environments, using platforms such as ServiceNow AIOps/ITOM, Dynatrace, Datadog, or equivalent internally developed solutions.
• Practical understanding of applying ML and GenAI to operations, including anomaly detection, incident correlation, LLM-assisted troubleshooting, incident summarization, and runbook automation.
• Experience coordinating resolution across third-party hosting providers, SaaS vendors, and internal application teams.
• Strong communication and interpersonal skills, with the ability to translate technical issues into business impact for executive stakeholders.
• Ability to work collaboratively with client engineering teams, mentor others, explain technical decisions, and facilitate knowledge transfer.
• A proactive, curious, and improvement-oriented mindset, with a demonstrated willingness to learn emerging technologies and challenge existing processes.
• Ability and willingness to work onsite at an enterprise client location in Irvine, CA.
• Willingness and eligibility to transition to full-time employment following the contract period.

Nice to Have

• Experience supporting hybrid data environments undergoing migration from legacy ETL and data warehouse platforms to modern cloud data stacks.
• Working knowledge of MicroStrategy or a comparable enterprise BI platform, including support of reporting and analytics operations.
• Experience with Power BI or enterprise BI modernization initiatives.
• Familiarity with Python or PySpark for operational tooling, data processing, and automation.
• Exposure to cloud cost management and FinOps practices, particularly Snowflake credit optimization.
• Experience introducing observability, alert-quality reviews, and toil reduction into an inherited production support environment.
• ITIL certification or equivalent practical grounding in service management.
• Experience with managed ingestion and transformation tools such as Fivetran, Airbyte, Matillion, and dbt.
• Experience supporting Db2, Informatica PowerCenter, or enterprise data platform modernization initiatives.
• Familiarity with enterprise ERP integrations or modernization involving Oracle Fusion, JD Edwards, or AS/400 environments.
• Previous experience in professional services, consulting, managed services, or forward-deployed engineering roles.
• Exposure to cloud platforms and AI ecosystems used to build and deploy enterprise agentic workflows.