AuxoAI is a global platform-based servicesfirm. We help companies turn their strategies into practical digital and AIsolutions. By understanding how our clients make decisions, we use digital andArtificial Intelligence (AI) technologies to drive growth, enhance operations,improve customer experiences, and provide clear, actionable insights from theirdata.
We work across industries such ashealthcare, high-tech, consumer packaged goods (CPG), finance, and more acrosssales, marketing, and customer support functions. We help our clientsaccelerate their digital and AI journeys through:
• AI Application Development • Data, Digital and Cloud acceleration using AI • AI Native Product Engineering
We are looking for an AI-native Data OpsLead to own the end-to-end health of a client's enterprise data estate,operating as the single accountable control tower across a hybrid platform.What distinguishes this role is how you get there: you will build a servicethat detects, correlates and increasingly resolves on its own, applying AIOpsand GenAI to compress triage, predict failure on the critical path, and convertrepetitive manual intervention into automation — while keeping human judgmentat the decision gates that matter.
The role requires the candidate to exhibitengagement and technical leadership in equal measure. You will be the face ofthe service to client IT and business leadership, run the governance cadenceand hold the delivery relationship.
Engagement& Client Leadership
- Act as the primary point ofaccountability to client IT leadership and business data owners for theend-to-end data service across both the legacy and modern stacks.
- Chair the operationalgovernance cadence — daily stand-up, weekly cross-party operations review, ,monthly business reviews — and own the agenda, decisions and follow-through.
- Own the service scorecard andits narrative: SLA attainment, MTTR, data freshness, repeat-failure rate, passrate, connector stability and FinOps.
- Protect the scope boundarybetween run and change: route enhancement demand through governance, size andshape change requests.
- Lead client communicationduring major incidents and own the post-incident review.
ServiceOwnership & Operations
- Own the Standard OperatingProcedure for the estate — scope, monitoring framework, severity matrix, RACI,escalation paths, notification matrix and closure criteria — and keep itcurrent as the platform evolves.
- Lead triage on P1 and P2incidents, assign the resolver domain, run the cross-party bridge
- Drive problem management —convert recurring incidents into permanent fixes, and burn down the problembacklog
TechnicalLeadership
- Set the technical standard forthe service across legacy and modern technical stacks.
- Own the data architecturestandards for the estate, govern the data model — dimensional design, conformeddimensions and business keys, SCD treatment, and semantic consistency
- Lead diagnosis on majorincidents across domain boundaries — distinguishing an ETL fault from adatabase fault, a connector fault from a source schema change, a report failurefrom warehouse contention.
- Own all operational decisions,define monitoring and data-quality framework
- Establish AIOps for theservice, advance the service toward predictive and self-healing operations
- Review new business demands,own screening and qualifications of the demand, effort sizing andimplementation roadmap
Requirements
- Bachelor’s/Master’s degree inComputer Science, Engineering, or related field (or equivalent practicalexperience).
- 10–15 years in dataengineering, data warehousing or data operations, with experience of working inmanaged service or Data Operations function.
- Demonstrated experience as aclient-facing lead — running governance forums, owning SLAs and servicereporting, and managing escalations with senior IT and business stakeholders.
- Experience in InformaticaPowerCenter and a relational data warehouse platform.
- Working expertise across amodern cloud data stack — Snowflake, dbt, and a managed ingestion tool such asFivetran, Airbyte or Matillion.
- Strong SQL and data modellingexpertise, including dimensional modelling and warehouse performance tuning.
- Practical experience withenterprise job scheduling (Tidal, Control-M, Autosys or equivalent) and withITSM process in ServiceNow — incident, problem, change and major incidentmanagement.
- Proven ability to define andoperate a monitoring and alerting framework that measures data delivery, notjust job execution.
- Experience implementing AIOpsor intelligent observability in a production environment —using platforms suchas ServiceNow AIOps/ITOM, Dynatrace, Datadog or an equivalent in-house build.
- Practical grasp of how to applyML and GenAI to operations: baselining and anomaly detection on time-seriesoperational data, log and incident clustering, and LLM-assisted triage,incident summarisation or runbook generation.
- Experience coordinatingresolution across third-party hosting providers, SaaS vendors and internalapplication teams.
- Excellent written and verbalcommunication — able to translate a technical fault into business impact for anexecutive audience.
- Based in or willing to relocateto the Irvine / Los Angeles area, with the ability to be onsite with the clientas the engagement requires.
- Working knowledge ofMicroStrategy or a comparable enterprise BI platform.
- Familiarity with Python orPySpark for operational tooling and automation.
- Exposure to cloud costmanagement and FinOps practice, particularly Snowflake credit optimisation.
- Experience introducingobservability, alert-quality review and toil reduction into an inheritedsupport estate.
- ITIL certification orequivalent practical grounding in service management.