Siemens

Principal Data Engineer

Siemens$149K — $256K *
Enterprise Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in computer science, engineering, information systems, data engineering, or a related field, or equivalent practical experience.
  • 8+ years of experience in data architecture or cloud data platforms with enterprise-scale designs.
  • Expertise in Snowflake, dbt, SQL, and cloud-native data patterns.
  • Hands-on knowledge of Apache Superset for enterprise deployment and dashboard development.
  • Experience with manufacturing and asset-intensive data management.
  • Knowledge of government/public-sector data standards.
  • Experience in designing data governance and privacy frameworks.
  • Ability to communicate complex technical concepts and influence cross-functional teams.

Responsibilities

  • Lead the strategy and design for enterprise Data Cloud capabilities focused on analytics and reporting.
  • Design scalable data systems for optimal data ingestion and transformation processes.
  • Provide technical direction for Snowflake and dbt, overseeing architecture and performance.
  • Architect secure Data Share solutions and manage product onboarding activities.
  • Lead the architecture and administration of Apache Superset for performance optimization.
  • Drive advances in data governance and compliance practices.
  • Ensure platform reliability through operational monitoring and automation.
  • Translate asset-management needs into effective data models and mentor engineering teams.

Benefits

  • Comprehensive health and wellness benefits package.
  • Access to employee wellness programs and resources.
Full Job Description
Description

As Principal Data Cloud Architect, you will lead the design, governance, and evolution of enterprise Data Cloud capabilities that support analytics, AI, reporting, and secure data sharing. You will combine hands-on data system design with technical leadership across Snowflake, dbt, Apache Superset, platform administration, observability, lineage, and governance. You will partner with product, engineering, BI, AI, security, and operations teams to deliver scalable solutions for manufacturing, government, and other asset-intensive customers.

You'll make an impact by

  • Leading Data Cloud strategy, standards, and solution design across enterprise data, analytics, AI, and reporting initiatives.
  • Designing scalable data systems, including ingestion, transformation, logical and physical models, semantic layers, and governed consumption patterns.
  • Providing technical direction for Snowflake and dbt architecture, administration, performance, security, cost management, and release practices.
  • Architecting and supporting secure Data Share solutions, summary views, account provisioning, entitlement workflows, and product onboarding.
  • Leading Apache Superset architecture, administration, semantic modeling, dashboard enablement, performance optimization, and migration from legacy BI platforms.
  • Advancing data governance, metadata, privacy, anonymization, retention, access controls, quality monitoring, and compliance practices.
  • Driving platform reliability through observability, lineage, monitoring, alerting, incident readiness, and operational automation.
  • Supporting commercial and government cloud environments while partnering with security and infrastructure teams on compliant platform designs.
  • Translating manufacturing and government asset-management needs into durable data models for assets, facilities, infrastructure, maintenance, work management, inspections, lifecycle planning, reliability, and capital planning.
  • Mentoring engineers and collaborating across global product and delivery teams to move designs from concept through production.

This is how you'll win us over

  • Bachelor's degree in computer science, engineering, information systems, data engineering, or a related field, or equivalent practical experience.
  • 8+ years of progressive experience in data architecture, cloud data platforms, data engineering, or closely related roles, including ownership of enterprise-scale designs.
  • Demonstrated expertise with Snowflake, dbt, SQL, dimensional and normalized data modeling, data integration, and cloud-native data platform patterns.
  • Hands-on knowledge of Apache Superset, including enterprise deployment, administration, security, semantic datasets, dashboard development, performance tuning, and integration with cloud data warehouses.
  • Demonstrated expertise with manufacturing and asset-intensive data, including asset hierarchies, equipment, facilities, maintenance, work orders, reliability, inspections, inventory, and lifecycle information.
  • Demonstrated expertise with government or public-sector asset data, including infrastructure inventories, facilities, compliance, capital planning, budgeting, and governed reporting.
  • Experience designing data governance, metadata, lineage, privacy, access-control, retention, and anonymization capabilities.
  • Experience with platform observability and operational practices, including monitoring, alerting, solving, reliability, and production support.
  • Ability to communicate complex technical decisions clearly and influence partners across product, engineering, analytics, AI, security, and business teams.
  • Ability to work effectively across a globally distributed organization and lead through technical influence.

Qualified Applicants must be legally authorized for employment in the United States. Qualified Applicants will not require employer- sponsored work authorization now or in the future for employment in the United States.

You'll thrive even more if you also bring

  • Experience modernizing analytics from Qlik or other legacy BI platforms to Apache Superset or comparable open analytics platforms.
  • Experience with AWS data services, GovCloud environments, Snowflake Streamlit, Grafana, OpenLineage, or similar technologies.
  • Knowledge of Salesforce account, opportunity, entitlement, and customer-product data integration patterns.
  • Experience supporting enterprise asset management, computerized maintenance management, facilities management, or asset performance management products.
  • Understanding of AI/ML data enablement, MLOps integration, agentic analytics, data catalogs, business glossaries, and governed self-service analytics.
  • Experience establishing architecture standards, design reviews, operating models, or technical roadmaps for Data Cloud platforms.

What success looks like

  • You will strengthen Data Cloud continuity, improve platform governance and reliability, enable modern Superset analytics, and deliver reusable data designs that serve manufacturing and government asset-management use cases.

You'll Benefit From
Siemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $149,511 - $256,304 annually with a target incentive of 20% of the base salary. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location.

About Siemens

Siemens AG is a German multinational conglomerate company headquartered in Munich and the largest industrial manufacturing company in Europe with branch offices abroad. The principal divisions of the company are Industry, Energy, Healthcare, and Infrastructure & Cities, which represent the main activities of the company. The company is a prominent maker of medical diagnostics equipment and its medical health-care division, which generates about 12 percent of the company's total sales, is its second-most profitable unit, after the industrial automation division. The company is a component of the Euro Stoxx 50 stock market index. Siemens and its subsidiaries employ approximately 385,000 people worldwide and reported global revenue of around €87 billion in 2019 according to its earnings release.
Learn more about Siemens
Size
305,000 employees
Industry
Founded
1847
NASDAQ

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