Data Architect

The Data Architect is responsible for designing and evolving the overall data architecture that supports the organization's data platforms, pipelines, and analytics ecosystems. This role focuses on building scalable, secure, and high-performance architecture across cloud and hybrid environments to enable reliable data delivery and advanced analytics. The Data Architect collaborates with data engineers, governance leads, and business stakeholders to ensure data infrastructure aligns with enterprise goals and modern architectural best practices.

Key Responsibilities:

Data Infrastructure Architecture

• Design and implement scalable data architectures across cloud and on-premise environments.
• Define architecture standards for data lakes, data warehouses, real-time streaming, and batch data processing.
• Ensure alignment of architecture with performance, security, scalability, and availability requirements.

Modern Data Integration

• Define architectural blueprints for integrating data across operational systems, SaaS platforms, and analytics environments.
• Recommend and lead modernization efforts, including cloud migration, data platform upgrades, and containerization.
• Promote adoption of emerging patterns such as data mesh, lakehouse, or serverless data processing architectures.
• Oversee orchestration on system-level flow across ingestion, transformation, and consumption layers.

Governance Compliant and Documentation

• Ensure architectural compliance with data security, access control, and data privacy standards.
• Work with governance and compliance teams to embed policy enforcement mechanisms in architecture designs.
• Translate strategic data needs into long-term architectural solutions.

Collaboration and Documentation

• Partner with engineers, analysts, and business units to align architecture with data-driven initiatives.
• Support implementation teams with architectural reviews and guidance throughout the development lifecycle.
• Stay updated on technology trends to inform architectural direction and promote innovation.
• Document architecture principles and enforce standardization across teams and projects.

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field.
• 10+ years of experience in data architecting, data integration, or data pipeline development roles.
• Proven experience developing and maintaining scalable, reliable data solutions.
• Hands-on experience with cloud services (e.g., AWS, Azure, or GCP) for data storage.
• Familiarity with infrastructure-as-code and CI/CD practices for data engineering (e.g., Terraform, Jenkins).
• Solid understanding of relational and non-relational data bases.
• Knowledge of modern data warehouse and lakehouse architectures (e.g., Snowflake, Databricks, etc).
• Experience working with modern data platforms and ETL/ELT pipelines.
• Familiarity with version control systems such as Git/GitHub.
• Exposure to Agile or DevSecOps methodologies in data engineering projects.
• Ability to translate technical data requirements into functional data solutions.
• Good communication and collaboration skills across technical and non-technical teams.

Preferred

• Master's degree in Data Science, Information Systems, Business Analytics, or a related field.
• Experience with data cataloging, lineage, or metadata management tools.
• Relevant certifications (e.g., AWS Certified Data Engineer, Google Professional Data Engineer, Microsoft Azure Data Engineer Associate).

Job Types: Full-time, Permanent

Benefits:

• Life insurance
• Opportunities for promotion
• Promotion to permanent employee

Application Question(s):

• What is your expected salary?

Education:

• Bachelor's (Preferred)

Experience:

• data architecting or data integration: 10 years (Preferred)
• developing and maintaining data solutions: 10 years (Preferred)
• cloud services: 9 years (Preferred)

Willingness to travel:

• 100% (Preferred)

Work Location: In person