Working Student contributing to data engineering projects for AI/ML workflows while gaining hands - on experience with data pipelines and tools.
About the role
- Data Architect leading modernization of the data ecosystem using dbt and Snowflake. Designing scalable solutions for real-time analytics and enterprise-scale reporting.
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 Snowflake; 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.
Requirements
- 8+ years in data architecture, with deep experience in cloud-based data platforms.
- Strong hands-on experience with Snowflake and dbt (must-have).
- 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.
- Experience in platform modernization and cloud migration projects.
- Familiarity with tools like Airflow, Terraform, Great Expectations, or Monte Carlo.
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
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