Data Architect - Remote

Mindex•Rochester, NY

8d•$120,000 - $173,000•Remote

About The Position

Mindex, a software development and cloud services company with over 30 years of success, is seeking a Data Architect to design scalable, secure, and high-performing data solutions. This role is crucial for shaping data strategy to support analytics, reporting, AI, and other data-driven initiatives. The ideal candidate will lead architecture discussions, establish data standards, and collaborate with both technical and business stakeholders. Responsibilities include designing and optimizing modern data platforms, ensuring data systems are reliable and aligned with business goals, and creating a foundation for future growth. The position is remote.

Requirements

BS degree in Computer Science, Data Science, Engineering, or equivalent software/services experience required
8+ years of progressive experience in data engineering, data architecture, or related disciplines, including enterprise-scale data solution design
5+ years of hands-on experience designing and implementing modern data platforms using technologies such as Snowflake, Databricks, Spark, or similar distributed data systems
Strong experience (5+ years) in Python, SQL, PySpark, R, or comparable languages for large-scale data processing and analytics
Proven experience architecting, building, and optimizing complex data pipelines, data ecosystems, and large, multi-source data environments
3+ years of experience designing and supporting cloud-based data architectures, with a strong preference for Microsoft Azure (e.g., Azure Data Factory, Data Lake, Databricks, Spark, Azure ML, Cosmos DB)
Demonstrated experience leading or influencing architecture decisions and establishing standards for scalable, secure, and high-performing data solutions
Experience implementing data governance, data security, privacy, and compliance frameworks in enterprise environments
Hands-on experience with Agile methodologies and leading technical design within Agile delivery teams
Experience with CI/CD, DevOps, and infrastructure-as-code practices (e.g., Azure DevOps, Terraform, ARM, GitHub Actions, Ansible Tower), including establishing automation and deployment standards
Experience integrating enterprise systems and platforms, including Salesforce FSC and/or Salesforce Data Cloud
Proven ability to mentor engineering teams and influence technical strategy, best practices, and architectural direction
Strong expertise in data architecture design, including data lakes, warehouses, and streaming systems
Advanced proficiency in SQL and distributed data processing frameworks (e.g., Spark, Databricks)
Experience with Microsoft Azure and modern cloud-based data platforms
Knowledge of ETL/ELT design patterns and data integration best practices
Familiarity with data modeling techniques (dimensional, normalized, Data Vault, etc.)
Knowledge of CI/CD pipelines, infrastructure as code, and MLOps practices
Understanding of API integrations and enterprise system connectivity
Applicants must be authorized to work for ANY employer in the U.S. We are unable to sponsor, or take over, sponsorship of an employment Visa at this time.

Responsibilities

Design and implement scalable, high-performance data architectures across cloud and hybrid environments
Define and enforce data modeling standards, including conceptual, logical, and physical data models
Build and optimize enterprise data pipelines and data integration frameworks to support analytics and operational use cases
Architect and manage data platforms leveraging technologies such as Snowflake, Databricks, Spark, and Azure Data services
Collaborate with data engineers, data scientists, and business stakeholders to translate business needs into robust data solutions
Establish and maintain data governance, data quality, and metadata management frameworks
Ensure data privacy, security, and compliance requirements are met across all platforms and pipelines
Lead architecture decisions for data storage solutions including data lakes, data warehouses, and real-time data processing systems
Optimize performance and cost efficiency of data platforms and workloads
Support Agile delivery frameworks and contribute to sprint planning, backlog grooming, and architectural roadmaps
Implement and oversee CI/CD pipelines and infrastructure-as-code practices for data solutions
Evaluate emerging technologies and recommend solutions to enhance data capabilities