Enterprise Data Architect

At Constant Contact, we are seriously awesome people who take ownership and make an impact by operating with the mindset, integrity and courage of a small business owner. There’s something so profoundly rewarding about knowing that your work is empowering people everywhere to pursue their dreams.  Here, we all play an integral part in helping business owners, entrepreneurs, non-profits and individuals to succeed by giving them all the help and tools they need to grow online. We’re energized by new challenges and new possibilities-and we’re just getting started!

We have an opening for an Enterprise Data Architect to help lead the design, implementation, and evolution of our global data platform. As a SaaS company providing digital marketing solutions to small businesses worldwide, we are scaling our platform to support AI, machine learning, in-app analytics, and real-time data products.

This role is both strategic and hands-on: you will define the standards, blueprints, and governance models for our enterprise data architecture while also contributing directly to development, schema design, and infrastructure optimization. You will play a key role in data architecture implementation across domains and will partner with engineering, product, data science, and AI teams to ensure our data platform enables innovation, compliance, and scalability. This role ensures that all data-related systems, initiatives, and assets are integrated and aligned with the company's business goals, regulatory requirements, and long-term vision. 

The Enterprise Data Architect will report to the Senior Director of Enterprise Data Platform and work closely with data engineers, ML engineers, software engineers, and data governance leads.

What You'll Do:

Architect & Implement Data Mesh or Medallion Architecture

• Define and roll out domain-driven data product architecture across the enterprise.
• Establish standards for data contracts, schemas, SLAs, lineage, and discoverability (with DataHub).
• Records detailed logical and physical data models in the information repository and coordinates the publication and maintenance of these models.

Strategic Data Platform Design

• Define the overall vision, strategy, and roadmap for the organization's data architecture, aligning it with enterprise business objectives.
• Develop and maintain the enterprise data architecture roadmap across AWS, Snowflake, and hybrid systems.
• Design scalable solutions for real-time analytics, in-app data products, and AI/ML pipelines.
• Design and maintain the blueprint for the entire data ecosystem, which includes conceptual, logical, and physical data models for various systems and domains.
• Assess and recommend the data technologies, platforms, and tools—including cloud solutions (AWS, Azure, GCP), databases (SQL and NoSQL), and analytics platforms—that best meet the organization's needs. 

Hands-On Engineering

• Write and optimize scripts, build scalable data pipelines, and design schemas in Snowflake and Iceberg/S3.
• Optimize data infrastructure performance and cost (Athena, Trino, DuckDB, Cube.dev, Superset, Tableau)

Data Governance, Compliance & Security

• Collaboration with data governance leads to enforcing policies on PII, GDPR, CCPA, and international data residency.
• Implement standards for encryption, row/column masking, lineage tracking, and auditability.
• Ensure compliance is embedded into architectural patterns (AWS Lake Formation, IAM, Glue Catalog, etc.).

Blueprints & Standards

• Create reusable architecture patterns and design templates for ingestion, transformation, serving, and quality.
• Work with engineering teams to enforce consistency in tools, pipelines, and naming conventions.

Collaboration & Influence

• Partner with domain teams (Marketing, Finance, Product, Deliverability, etc.) to ensure domain ownership of data products.
• Work closely with ML/AI teams to enable model training, feature store integration, and real-time inference pipelines.
• Provide architectural leadership across global teams and mentor engineers on best practices.

Who You Are:

• Experience: 12+ years in data architecture, data engineering, or related fields; with at least 5+ years in an architect-level role.
• Tech Expertise:
• • Strong hands-on SQL, Python, or other data centric programming language.
  • Deep experience with AWS data stack (S3, Glue, Athena, Lake Formation, Kinesis/MSK, EMR/Trino, IAM).
  • Exper