Data Engineering Lead

Tredence Inc.; San Jose (CA); On-site; USD 170,000 - 230,000; Full time

Job summary

Tredence Inc. is hiring a Senior Data Engineering Lead to drive the Data Foundation and Platform Modernization using a Databricks Lakehouse architecture. You will define enterprise data standards and a Unified Data Model for SCM, while guiding cross-functional teams to deliver scalable, governed data solutions.

The role requires deep expertise in Databricks technologies, data modeling, governance, and leading large data transformation programs with onsite and offshore teams.

Qualifications

• Extensive experience with Databricks ecosystem and lakehouse patterns.
• Experience designing Medallion Architecture (Bronze, Silver, Gold).
• Strong governance, metadata, security, and data quality discipline.
• Leadership of large-scale enterprise data transformation programs.

Responsibilities

• Lead modernization of data platform using Databricks Lakehouse architecture.
• Drive migration from legacy to cloud-native data ecosystems.
• Define enterprise data standards and Unified Data Model for SCM.
• Oversee data governance, metadata, lineage, and security.
• Mentor onsite and offshore engineering teams and align with executives.

Skills

Databricks Lakehouse

Unity Catalog

Databricks SQL

PySpark

Data Modeling

Data Warehousing

Semantic Layer Design

Medallion Architecture

Data Governance

Metadata Management

Data Quality Frameworks

Security & Access Controls

Data Platform Modernization

Leadership & Delivery

Enterprise Data Transformation

Tools

Databricks Lakehouse

Unity Catalog

Databricks SQL

PySpark

Job description

Tredence enables organizations to transform data-driven insights into business actions by combining deep expertise in business analytics, data science, and software engineering. As a trusted partner to leading global enterprises, Tredence delivers scalable prediction, optimization, and AI-driven solutions that empower organizations to make better decisions and drive measurable business outcomes. Headquartered in the San Francisco Bay Area, Tredence serves clients across North America, Europe, and Southeast Asia. Learn more at www.tredence.com.

About the Role

Tredence is seeking a Senior Data Engineering Lead to spearhead a strategic Data Foundation and Platform Modernization initiative. This leadership role will be responsible for designing and implementing a modern Databricks Lakehouse Platform, establishing enterprise-wide data standards, and defining a Unified Data Model (UDM) for the Supply Chain Management (SCM) domain. The ideal candidate will combine deep technical expertise with architectural leadership, enabling the transformation of complex data ecosystems into scalable, governed, and business-ready data platforms.

Responsibilities

• Data Platform Modernization
• Lead the design and implementation of a modern enterprise data platform leveraging the Databricks Lakehouse architecture.
• Drive migration and modernization initiatives from legacy platforms to cloud-native data ecosystems.
• Define best practices for scalability, performance, reliability, security, and cost optimization.
• Design and govern a comprehensive Supply Chain Management (SCM) Unified Data Model spanning source systems, ingestion, transformation, semantic, and consumption layers.
• Establish enterprise standards across Bronze, Silver, Gold, and Semantic layers following Medallion Architecture principles.
• Ensure alignment of business definitions, metrics, and reporting standards across the organization.
• Data Governance & Quality
• Implement robust data governance frameworks covering metadata management, lineage, security, and compliance.
• Define and enforce enterprise data quality standards, validation processes, and monitoring mechanisms.
• Promote reusability of data assets and enterprise-wide data stewardship practices.
• Leadership & Delivery Management
• Lead and mentor high-performing onsite and offshore engineering teams.
• Drive architectural decisions, technical standards, and delivery excellence across multiple workstreams.
• Foster a culture of innovation, collaboration, and continuous improvement.
• Stakeholder Collaboration
• Partner with business leaders, product owners, and technical stakeholders to understand strategic priorities and translate them into scalable data solutions.
• Serve as a trusted advisor for data strategy, platform transformation, and analytics enablement initiatives.
• Communicate architectural vision, progress, risks, and recommendations to executive stakeholders.

Qualifications

• Extensive experience with the Databricks ecosystem, including:
• Databricks Lakehouse
• Unity Catalog
• Databricks SQL
• PySpark
• Strong expertise in:
• Data Modeling and Data Warehousing
• Semantic Layer Design
• Data Platform Modernization
• Proven experience designing and implementing Medallion Architecture (Bronze, Silver, Gold) patterns.
• Strong understanding of:
• Data Governance
• Metadata Management
• Data Quality Frameworks
• Security and Access Controls
• Demonstrated ability to lead large-scale enterprise data transformation programs.

Preferred Skills

• 12+ years of experience in Data Engineering, Data Architecture, Data Platform Modernization, or related disciplines.
• Proven track record leading enterprise-scale Databricks Lakehouse implementations.
• Experience designing Supply Chain Management (SCM) data models and semantic consumption layers.
• Strong consulting and client-facing experience with the ability to influence senior stakeholders.
• Excellent leadership, communication, and problem-solving skills.
• Experience managing globally distributed teams and complex technology programs.