Semiconductor Industry

Marvell Technology•Santa Clara, CA

4d•$111,070 - $166,400

About The Position

The MBE AI Strategy & Enablement team drives engineering productivity and operational excellence across Marvell’s Software & Firmware Division. We also define and track the metrics that matter - from developer efficiency to lifecycle impact - providing leadership with the insights needed to make high-confidence decisions at scale. Our work touches every major engineering function, giving you a front-row seat to how data shapes strategy across a global organization.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Business Analytics, or related field.
5+ years in engineering analytics, BI development, or program reporting (semiconductor/hardware preferred).
Strong proficiency with Power BI (or equivalent) and dashboard design for executive audiences.
Strong hands-on experience with Jira (JQL, boards, dashboards) and Agile metrics.
Strong SQL skills for data extraction/transformation and building trusted datasets.
Experience integrating multiple data sources (BI + “system of record” tools) and working with data owners/IT.
Ability to define KPIs and communicate insights clearly to senior leadership and non-technical stakeholders.
Familiarity with product/AI metrics (adoption, cost, performance, quality) and how to operationalize them in reporting.

Nice To Haves

Python (or similar) for data processing/automation.
Experience with Databricks (or equivalent data platform) and multi-site/global reporting.
Experience with capacity planning/resource tools (e.g., P6) and cost modeling.
Exposure to AI/LLM telemetry/observability signals (usage, latency, cost, quality/evals) and integrating them into dashboards.
Experience building metric definitions/scorecards used across multiple teams (governance + adoption).

Responsibilities

Build and maintain executive- and team-level dashboards using Power BI, Jira dashboards, and other internal reporting systems.
Develop sprint and delivery dashboards (velocity, burn-down, throughput/flow, scope change, defect trends, predictability).
Create org-level dashboards for headcount/capacity, cost trends, and forecasting (partnering with Finance/Resource Planning).
Build program tracking dashboards for key initiatives (milestones, status, risks, dependencies, and delivery health).
Build and maintain AI initiative dashboards (PoC → pilot → production) including adoption, usage, cost, latency, quality, and guardrail/incident signals.
Define and standardize KPI definitions across teams; ensure consistency in how metrics are calculated and reported.
Integrate data from Jira and other internal systems (e.g., planning tools, internal data platforms, engineering systems) into reliable BI datasets.
Identify trends/anomalies and provide concise executive readouts with recommended actions.
Improve data quality (validation checks, reconciliations, source-of-truth alignment) and reduce manual reporting.
Maintain lightweight documentation for dashboards (data sources, logic, definitions, ownership).