Data Architect

Purpose of This Role:

We are seeking an experienced Data Architect to lead the design, implementation, and management of scalable and high-performance data architectures across the organization. This individual will play a critical role in integrating disparate data systems, establishing robust data governance frameworks, and aligning data strategies with business objectives. The ideal candidate combines technical expertise with strategic thinking and a deep understanding of modern data technologies.

Essential Duties and Responsibilities:

• Design and architect complex, scalable data systems in alignment with business goals and industry best practices.

• Collaborate with cross-functional teams to define data requirements, develop data models, and implement governance and compliance frameworks.

• Evaluate and integrate new data technologies and tools to improve data processing, scalability, and system performance.

• Provide technical leadership and mentorship to junior data engineers and architects.

• Conduct data analysis and profiling to identify trends, patterns, and opportunities for system optimization.

• Ensure data governance, security, and compliance with applicable regulations and internal policies.

• Establish and maintain data quality standards across systems and data pipelines.

• Design and oversee seamless data flow between systems and applications with a focus on performance and scalability.

• Promote a culture of innovation, continuous learning, and collaboration within data teams.

Knowledge, Skills, and Abilities:

• Bachelor’s degree in Computer Science or related field, or 8–10 years of experience in data architecture, data engineering, or a related discipline.

• Proven experience designing and implementing data models and data warehouses using platforms such as Snowflake, Redshift, or BigQuery.

• Hands-on experience with ETL tools such as Apache NiFi, Talend, or Informatica.

• Strong knowledge of data modeling, database design, system integration, and standardization principles.

• Experience with big data technologies such as Hadoop, Kafka, or equivalent, as well as hybrid (cloud/on-premise) architectures.

• Proficiency in SQL and scripting languages such as Python, R, or Scala.

• Familiarity with NoSQL databases such as MongoDB or Cassandra.

• Understanding of machine learning concepts and their relevance in enterprise data environments.

• Certifications in data architecture or cloud technologies (e.g., AWS, GCP, Azure) are a plus.

Training and Experience:

• Deep understanding of data governance, data quality, and data lifecycle management.

• Strong problem-solving skills with the ability to align technical solutions with business needs.

• Experience with real-time data streaming technologies such as Kafka or Kinesis.

• Track record of mentoring and guiding junior team members in best practices and innovation.

Conditions of Work:

• Ability to sit or stand for extended periods.

• Ability to remain focused and work on computers for the majority of the day.

• Willingness to work extra hours on short notice to meet deadlines.

• Ability to travel domestically if needed.