[Hiring] Senior Customer Data Platform Engineer @Modus Create

Role Description

The Customer Data Platform (CDP) Engineer will play a critical role within our client’s data engineering team, leading the design, implementation, and optimization of scalable data solutions. This position focuses on building robust data pipelines and curated data models within Snowflake, leveraging event-driven architectures and modern serverless infrastructure on Amazon Web Services, and enabling seamless integration with Salesforce Data Cloud.

The role is responsible for ensuring high data quality, governance, and secure access, while supporting advanced analytics and activation use cases that drive business growth and strategic decision-making. The ideal candidate combines deep expertise in event-driven architectures, serverless integration patterns, and modern data engineering practices with strong analytical thinking and communication skills.

This is a fully remote role with collaboration across distributed teams and daily overlap with the US Eastern Time Zone.

Responsibilities

• Design, develop, and maintain scalable ELT/ETL pipelines that ingest, transform, and publish data into Snowflake from internal and external sources.
• Partner with product, analytics, and application teams to translate CDP and data requirements into well-modeled data in Snowflake, using scalable and cost-efficient event-driven data pipelines.
• Design secure data access patterns for internal platforms (RBAC, masking policies, row access policies) and support privacy/compliance needs (e.g., GDPR, CCPA) across the data platform.
• Automate deployments and operational workflows using version control and CI/CD; maintain infrastructure as code and repeatable release processes for Snowflake objects.
• Document Snowflake architectures, data flows, and operational runbooks; stay current on Snowflake capabilities (e.g., Snowpipe, Streams/Tasks, Dynamic Tables); and recommend enhancements to improve reliability and scalability.

Qualifications

• Bachelor’s or Master’s degree in computer science, Information Systems Engineering, or a related field.
• 5+ years of professional experience in data engineering, with significant hands-on experience designing integrations with data warehousing and large databases (Snowflake preferred).
• Strong SQL skills and experience building curated schemas, semantic layers, and reusable data models for analytics and activation use cases.
• Proficiency with modern ELT/ETL and transformation patterns and tools (e.g., dbt or equivalent), including incremental processing and orchestration.
• Experience integrating Snowflake with external systems using APIs, file-based ingestion, or streaming/event patterns; familiarity with common integration/middleware platforms is a plus.
• Hands-on knowledge of cloud platforms (AWS, Azure, or GCP) as they relate to data storage, networking, security, and processing.
• Solid understanding of data governance, security, privacy, and compliance standards (e.g., GDPR, CCPA).
• Proven ability to analyze complex data sets and translate business requirements into technical solutions.
• Excellent problem-solving, communication, and project management skills.

Bonus points

• Snowflake certifications (e.g., SnowPro Core/Advanced) and/or cloud certifications (AWS, Azure, GCP) relevant to data engineering.
• Familiarity with reverse ETL and activation patterns to operational systems (e.g., marketing platforms, CRM) as part of a CDP ecosystem.
• Agile development experience and familiarity with DevOps practices (Git, CI/CD) for analytics engineering and database change management.

You’ll Love

• Building scalable data platforms that power AI and Machine Learning solutions.
• Working on high-impact, data-intensive systems with real-world scale.
• Collaborating closely with product and engineering teams to deliver meaningful outcomes.
• Raising the bar for data engineering best practices.
• Exploring modern cloud data tooling and continuously improving how data systems are built and maintained.