Full Stack Engineer

Full Stack Engineer

Project Role : Full Stack Engineer
Project Role Description : Responsible for developing and/or engineering the end-to-end features of a system, from user experience to backend code. Use development skills to deliver innovative solutions that help our clients improve the services they provide. Leverage new technologies that can be applied to solve challenging business problems with a cloud first and agile mindset.
Must have skills : Snowflake Data Warehouse
Good to have skills : NA
Minimum 3 year(s) of experience is required
Educational Qualification : 15 years full time education

Required Skills - Strong experience with cloud data platforms on AWS - Hands-on experience with Airflow, dbt, and Snowflake - Proficiency in SQL and Python - Experience working with S3-based data lakes (raw/curated patterns) - Familiarity with metadata management, data catalogs, and data governance concepts - Experience running data workloads on EKS / Kubernetes Preferred / Nice to Have - Pyspark and knowledge of Glue Catalog, IAM cross-account access, and secure data sharing - Experience implementing data quality frameworks (custom or open-source) - Exposure to hybrid / on-prem integrations (e.g., file drops, legacy ETL) - Experience with hybrid architectures (on-prem + cloud) Role Overview - The Data Platform Engineer owns the design, build, and evolution of the firm s cloud-native data platform. - This role focuses on ingestion, transformation, orchestration, metadata, and data quality across AWS and Snowflake. Core Responsibilities - Build and maintain data ingestion pipelines from internal and external sources into AWS S3 (Raw & Standard zones) - Develop and operate Airflow DAGs on EKS for ingestion, transformation, notifications, and data quality - Implement and maintain dbt models for Snowflake transformations - Manage Snowflake integrations, including external stages (S3) and environment separation (Prod / Non-Prod) - Own data quality frameworks, checks, and orchestration metadata (stored in RDS) - Integrate with AWS Glue / Data Catalog (SaaS) for metadata, lineage, and discovery with Atlan - Ensure data reliability, scalability, and cost efficiency across the platform - Partner with analytics and downstream consumers (BI tools, reporting, Cognos/Tableau)