Data Architect

Job Summary

We are seeking an experienced Data Architect with deep expertise in ETL/ELT design, Snowflake, and modern data architecture
. The ideal candidate will have a strong background in data modeling, governance, and cloud-based data platforms
, with the ability to standardize and streamline data engineering practices across teams. This role requires close collaboration with data engineers, analysts, and business stakeholders to design scalable, secure, and high-performing data solutions.

• Design and implement scalable data architectures supporting analytical and operational use cases across cloud platforms such as Snowflake, Big Query, or Redshift
  .
• Develop and optimize ETL/ELT pipelines for ingestion, transformation, and integration of large-scale structured and unstructured datasets.
• Define data modeling standards
  , governance policies, and architecture frameworks to ensure consistency, quality, and compliance.
• Collaborate with cross-functional teams to align data structures and implement data lineage, metadata management, and security frameworks
  .
• Establish best practices for data storage, performance optimization, and cost management in cloud environments.
• Partner with analytics and engineering teams to support data warehouse and lakehouse initiatives
  .
• Document architecture decisions, standards, and integration patterns for reusability and knowledge sharing.
• Participate in data platform modernization initiatives
  , contributing to the adoption of data mesh, lakehouse, and modern data stack principles
  .
• Provide technical leadership and mentorship to data engineering teams, driving standardization and automation.

• 7-10 years of experience in data architecture, data engineering, or BI architecture roles.
• Proven hands-on experience with Snowflake (schema design, performance tuning, compute optimization, and cost governance).
• Expertise in ETL/ELT tools and workflow orchestration (e.g.,
  Airflow, dbt, Glue, Informatica, Matillion
  ).
• Strong understanding of data modeling, warehousing concepts, and dimensional design (Star/Snowflake schema).
• Knowledge of data governance, lineage, security, and compliance frameworks
  .
• Experience with Python, SQL, or Spark for data transformation and pipeline development.
• Familiarity with modern data architectures such as data mesh, lakehouse, or data fabric
  .
• Excellent documentation, communication, and stakeholder alignment skills.
• Ability to work collaboratively with engineering, analytics, and business teams in an Agile environment.