2 hours ago
Carmel, IN, USAStaff+
Responsibilities
- Document how software applications generate, define, and use product data across business units.
- Define and implement a unified GSS product data model, including physical schemas, data interfaces, pipelines, semantic layers, and APIs.
- Maintain the authoritative product data catalog covering definitions, standards, storage, lineage, and ownership.
- Design data lake and digital-twin architectures for connected-device telemetry at scale.
- Create repeatable technical onboarding processes for business-unit products and systems.
- Establish and enforce data-model, lineage, quality, governance, and CI-gate standards.
- Audit product data implementations against shared platform standards and communicate architectural risks to senior leadership.
- Partner with product engineering, enterprise data, AI, identity, and security teams to enable governed data and agentic AI use cases.
- Review the data architecture for EU Cyber Resilience Act compliance and OSDP migration.
- Facilitate architecture reviews and enable product engineering teams to adopt shared data standards.
Requirements
- 8+ years of experience in data architecture, data modeling, or data engineering, including 3–5 years designing shared or central data platforms used by multiple product engineering teams.
- Experience translating conceptual or logical data models into physical architecture, pipelines, and APIs with product engineering teams.
- Experience building and maintaining an enterprise data catalog or comparable metadata and governance repository.
- Experience unifying data models and pipelines across independently operated business units or product lines at enterprise scale.
- Experience designing or operating technical data-onboarding processes for new business units, systems, or data domains.
- Hands-on experience with Databricks, Snowflake, or BigQuery; S3, ADLS, or GCS; Airflow or dbt; Kafka; SQL; and Python.
- Experience ingesting, aggregating, and modeling large-scale device or IoT telemetry using layered data zones.
- Track record of defining and adopting schema, lineage, quality, and governance standards without direct authority over participating teams.
- Understanding of metadata management, data cataloging, master data management, data governance, enterprise architecture frameworks, and DAMA-DMBOK.
- Ability to communicate technical and architectural risk in business terms and facilitate reviews across teams with different priorities.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience; master’s degree preferred.
- Legally authorized to work in the United States.
Benefits
- Health, dental, and vision insurance coverage.
- 401K plan with a 6% company match and no vesting period.
- Tuition reimbursement.
- Unlimited paid time off.
- Employee discounts through Perks at Work.
- Professional development, Clifton Strengths testing and coaching, and opportunities for community involvement.
- Work-life balance and an award-winning, inclusive workplace culture.
Tech Stack
Categories
Data Engineering
