Data Warehouse Architect

Data Warehouse Architect (Level 3)

We are seeking an experienced Data Engineering Lead/Data Warehouse Architect to lead the design, development, and maintenance of scalable data pipelines on cloud platforms such as AWS, Azure, or Google Cloud. The ideal candidate will excel in Lakehouse and Medallion Architecture concepts with deep expertise in distributed systems including Spark, Kafka, Kubernetes, Databricks, SageMaker, and DBT.

Key Responsibilities:

• Oversee the end-to-end lifecycle of data pipelines for analytics and operational ML applications.
• Architect and optimize infrastructure using Star-schema models to enable robust visualization in Power BI/Tableau.
• Enforce strict Data Sharing Policies and governance standards to ensure secure, versioned access control for data products.
• Mentor junior engineers and promote best practices within the DevOps framework (GitHub/Jenkins/Terraform).

Required Qualifications:

• Bachelor's degree in Computer Science or related field with a minimum of 4 years hands-on experience building ETL/ELT pipelines.
• Proven proficiency in Python, SQL, R, PySpark, and Terraform scripting for orchestration (DAGs/YAML).
• Demonstrated ability to hydrate enterprise data lakes from relational and unstructured sources into Parquet format within a Lakehouse architecture.

Tech Stack:

Key technologies include Databricks, Sagemaker, Spark, Kafka, Kubernetes, NoSQL/Graph DBs, Docker, Juniper Notebooks, and visualization tools like Power BI/Tableau. This role offers the opportunity to shape enterprise data strategy using cutting-edge AI/ML frameworks.