Enterprise Data Lake Specialist

Soho Square Solutions; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Soho Square Solutions is seeking an experienced Enterprise Data Lake Specialist to lead enterprise data architecture, data engineering, and CDP implementations. You will drive end-to-end data architecture for marketing activation, customer segmentation, and sales initiatives, collaborating with stakeholders and partners to establish enterprise-wide data standards.

The role emphasizes Databricks-driven ingestion and transformation, identity resolution, data quality governance, and scalable data

Qualifications

• Experience with CDP, enterprise data architecture and marketing data ecosystems.
• Experience designing data schemas, models, identity resolution, segmentation and activation workflows.
• Strong SQL and Python for data processing and troubleshooting.
• Knowledge of data governance, metadata management and data quality frameworks.

Responsibilities

• Lead end-to-end architecture and delivery for enterprise CDP implementations.
• Design and govern scalable data ingestion and transformation pipelines using Databricks.
• Define enterprise data models, schemas and activation logic across business units.
• Implement automated data quality checks, monitoring, and remediation strategies.
• Establish data governance standards, data lineage documentation, pipeline monitoring, and SLA compliance.
• Integrate marketing and customer data from platforms and enterprise data lakes.
• Lead technical requirements gathering, stakeholder discussions, and architecture reviews.
• Oversee implementation partner deliverables and ensure governance compliance.
• Create and maintain documentation covering pipelines, lineage, and governance policies.
• Lead knowledge transfer and best-practice adoption across teams.

Skills

CDP architecture

Databricks

SQL

Python

Data governance

Data modeling

Stakeholder mgmt

Tools

Jira

Confluence

GitHub

REST APIs

Job description

Job Title: Enterprise Data Lake Specialist

Location: 100% Remote

Job Summary:

We are seeking an experienced Enterprise Data Lake Specialist to lead enterprise data architecture, data engineering, and customer data platform implementations. The ideal candidate will have strong expertise in Databricks, customer data platforms (CDP), enterprise data modeling, data ingestion and transformation pipelines, and marketing data governance.

This role will drive end-to-end data architecture and technical delivery, ensuring high-quality, scalable, and reliable data pipelines that support marketing activation, customer segmentation, lead management, retention, and sales initiatives. The specialist will collaborate with business stakeholders, engineering teams, and implementation partners to establish enterprise-wide data standards and best practices.

Key Responsibilities

• Lead end-to-end architecture and technical delivery for enterprise customer data platform implementations, from data modeling and ingestion through downstream activation.
• Design, develop, and govern scalable data ingestion and transformation pipelines using Databricks to deliver production-ready curated datasets.
• Define and maintain enterprise data models, schema standards, identity resolution strategies, and activation logic across business units.
• Design and implement automated data quality validation frameworks, monitoring processes, and remediation strategies to address recurring data quality issues.
• Establish data governance standards, data lineage documentation, pipeline monitoring, and service-level agreement (SLA) compliance.
• Integrate marketing and customer data from platforms such as marketing automation systems, web analytics, and enterprise data lakes.
• Lead technical requirements gathering, stakeholder discussions, sprint planning, and architecture reviews for cross-functional initiatives.
• Serve as the technical lead and product owner for data platform implementations, translating business requirements into scalable technical solutions.
• Oversee implementation partner deliverables, review technical designs and code, and ensure adherence to enterprise architecture and governance standards.
• Create and maintain comprehensive documentation covering data pipelines, transformation logic, schema definitions, data lineage, and governance policies.
• Lead knowledge transfer, technical enablement, and best-practice adoption across engineering teams and implementation partners.
• Collaborate with marketing, sales, analytics, and engineering stakeholders to support customer segmentation, campaign activation, and business reporting use cases.

Required Skills and Qualifications

• Strong hands-on experience with customer data platforms (CDP), enterprise data architecture, and marketing data ecosystems.
• Experience designing and implementing data schemas, data models, identity resolution strategies, segmentation, and activation workflows.
• Strong Databricks experience, including data ingestion, transformation, pipeline development, and curated dataset creation.
• Proficiency in SQL and Python for data processing, validation, transformation, and troubleshooting.
• Experience with REST APIs and integrations between enterprise data platforms and downstream applications.
• Knowledge of enterprise data modeling, data governance, metadata management, and data quality frameworks.
• Experience implementing automated data quality checks, pipeline monitoring, error handling, and SLA tracking.
• Familiarity with marketing automation platforms, including Marketo, and web data integrations.
• Strong understanding of B2B marketing data architecture, customer identity management, and data activation workflows.
• Experience leading technical delivery, gathering stakeholder requirements, and coordinating with cross-functional teams.
• Strong technical documentation, communication, problem-solving, and stakeholder management skills.

Tools and Platforms

• Databricks
• Customer Data Platforms (CDP)
• Marketo and web data integrations
• SQL and Python
• REST APIs
• Jira and Confluence
• GitHub
• AI-assisted development tools, including Claude and Claude Code

Preferred Experience

• Experience supporting enterprise-scale B2B marketing data architecture and customer data initiatives.
• Experience with customer analytics, journey orchestration, audience segmentation, and marketing activation applications.
• Experience managing implementation partners and enforcing enterprise data standards across multiple teams.
• Experience working in Agile/Scrum environments with distributed engineering teams.
• Familiarity with customer analytics and B2B journey orchestration platforms.