Designs and leads modern, scalable data platforms using Snowflake, dbt, and AWS. Responsibilities include data modeling, batch and streaming pipelines, governance, security, privacy, migration from legacy systems, deployment automation, observability, testing, and enterprise reporting. The role collaborates with technical and business stakeholders, establishes architectural standards, mentors data engineers, and guides platform modernization while balancing performance, maintainability, scalability, and cost.
About the Role: We're seeking a strategic and hands-on Data Architect to design and implement scalable, secure, and modern data solutions across our organization. You'll play a critical role in leading the modernization of our data ecosystem using dbt, building a foundation for real-time analytics and enterprise-scale reporting in the cloud.
Responsibilities
- Architect and evolve our data platform using Snowflake as the central data warehouse and dbt for transformation logic.
- Design and implement batch and streaming pipelines, ensuring scalability and cost-efficiency in AWS.
- Establish best practices for data modeling, warehouse schema design, and semantic layer standardization using dbt.
- Define and enforce data governance, security, and privacy policies in alignment with compliance frameworks.
- Lead data migration from legacy sources to AWS; work closely with DevOps to automate and secure deployment processes.
- Collaborate with engineering, product, and business stakeholders to understand data needs and align solutions with business goals.
- Mentor and guide data engineers; support code reviews, architectural reviews, and team upskilling.
Qualifications:
- 8+ years in data architecture, with deep experience owning a modern data platform end to end: pipelines, storage, modelling, governance, monitoring.
- Expertise in data modeling (3NF, star/snowflake schemas), ELT/ETL design, and performance tuning.
- Solid understanding of AWS services (S3, Glue, Lambda, Redshift, Kinesis, etc.).
- Strong programming in SQL and Python; experience with CI/CD and data testing in dbt.
- Knowledge of data governance, lineage, metadata management, and data quality frameworks.
- Experience working with streaming technologies (Kafka, Kinesis) and large-scale datasets.
- Has modernised platforms and run migrations while keeping live systems running.
- Brings documentation, data quality, observability and testing as a default while balancing scalability, performance, maintainability and cost.
- Designs architecture and makes the technology calls, not just implements them. Sets common patterns and standards across application teams.
- Works comfortably across both engineering and business.
- Experience in platform modernization and cloud migration projects.
- Familiarity with tools like Airflow, Terraform, Great Expectations, or Monte Carlo.
Preferred Skills:
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