Chief Data Officer — Automotive-Chip Business

The mandate

An automotive-chip business is ramping products through external foundry, packaging and test routes, but engineers spend days reconciling wafer, die, lot, test, shipment and vehicle-return identifiers. Dashboards differ because test versions, exclusions and retest rules are not governed consistently. An urgent new Chief Data Officer will establish trustworthy evidence without turning data teams into product-disposition authorities.

Approximately 1,350 employees and material partners depend on the data perimeter. The CDO owns governance, architecture, integration, lineage, data products, analytical controls and talent and reports to the Group Chief Executive or sponsor. Engineering owns root cause and quality owns release.

Genealogy must survive wafer splits, assembly, rework, test insertion, binning and shipment. Missing links will be exposed rather than inferred silently. Supplier agreements require schema, timing, correction and retention.

Test context is fundamental. Programme version, limits, equipment, calibration and retest policy determine comparability. Historical results cannot be rewritten by a later master-data change.

Analytics will preserve population and exclusions. Models can rank hypotheses but cannot release product or narrow containment without authorised technical review. Drift and test change will trigger reassessment.

Customer returns require controlled linkage and privacy. Vehicle, customer and supplier data will be segregated by purpose, with evidence retained for audit and investigation.

Containment analytics must be reproducible. When a suspected failure population emerges, teams need versioned logic identifying related wafers, packages, test insertions, shipments and vehicles. Reviewer approval and preserved outputs will support customer action and later audit. Queries cannot quietly change as new data arrives.

Master data will receive maker-checker control. Product identities, test limits, units, bin maps and customer mappings can alter millions of records. Impact assessment, effective date and rollback are required, and direct production edits without reconstruction will be prohibited.

Data timeliness matters to safety and customer decisions. A complete dataset arriving after disposition has limited value. Use-case service levels will distinguish streaming and batch need, expose late supplier feeds and require emergency manual records to reconcile back to the governed source.

Model lifecycle will include drift, authorised use and retirement. A classifier trained during early ramp may become misleading after process or test change. Engineering owns technical suitability, while the data organisation preserves training population, performance, limitations and review date.

Resilience will test restoration of genealogy and containment services across cloud, local and partner connections. Backup alone is inadequate without compatible schema, identity, immutable source and practised recovery inside customer decision time.

Vehicle safety and regulatory record needs will shape retention. Data used to justify qualification, change and field action may need to remain reproducible for many years. The CDO will align archive, legal hold, access and deletion with product lifecycle and ensure format or vendor retirement does not make evidence unreadable.

Data-product economics will distinguish foundational control from optional analytics. Each product will have an operational owner, adoption evidence and retirement rule. Dashboards that do not change a decision will not compete indefinitely with genealogy, containment and supplier integration.

Stewardship will be distributed but accountable. Suppliers, engineering, quality and customer teams own meaning at source; the CDO provides standards, lineage and escalation. Data staff will not be asked to settle technical disagreements by selecting the most convenient value.

Data-quality exceptions will carry customer and product consequence, not only completeness scores, so teams resolve the records most capable of changing containment, qualification or release.

The role is new because current projects lack cross-chain authority. The onsite Dresden CDO will build product-oriented data teams close to engineering and quality.

What you will own

• Establish die-to-vehicle genealogy and source lineage.
• Govern test context, master data and corrections.
• Deliver reproducible yield and return analytics.
• Set supplier data and access controls.
• Validate analytical products and model lifecycle.
• Protect customer, vehicle and partner information.
• Prioritise data against live ramp decisions.
• Build data engineering and stewardship leadership.

The first 12 months

In the first 60 days, trace representative units and returns, document gaps and reconcile disputed metrics. Set authoritative definitions.

By month six, deliver controlled genealogy and test context for priority products and establish supplier-data agreements and exception ownership.

At twelve months, achieve 98% genealogy completeness, reduce analytical preparation time by 70% and lower unresolved data discrepancies by 80%. Root-cause cycles should fall 30%, with no customer or release decision relying on an untraceable model output.

What the sponsor will measure

• Physical units traceable across external steps.
• Yield metrics reproducible from governed populations.
• Test and retest context preserved.
• Data gaps exposed rather than statistically hidden.
• Customer information segregated appropriately.
• Engineers spending more time on physical cause.

The person

You bring 18–22 years in semiconductor data, product systems or manufacturing analytics, including automotive genealogy. You have connected outsourced supply and field-return evidence.

Your prior scope should include billions of test records or 1,000 employees and partners. Evidence must include a genealogy break, changed test context and a model challenged by source data.

Compensation and terms

Base compensation is €340,000–460,000 plus annual incentive and long-term incentive linked to genealogy, yield learning, controls and leadership. The permanent role is based onsite in Dresden and carries accountability to the Group Chief Executive or nominated executive sponsor. Prompt appointment is preferred.

Confidentiality

The business, products, suppliers, customers, vehicle data and models remain confidential. Detail follows fit, conflicts and signed confidentiality. Applicants must not approach partners to identify the enterprise.