We are looking for a Data Platform Engineer | AI (Remote) ️
To join a data platform modernization project, migrating reporting and analytics systems into a unified cloud architecture on AWS, using Snowflake as data warehouse and Python/Spark pipelines for data processing.
The platform aggregates data from financial systems, external APIs, and internal microservices, supporting real-time analytics, machine learning workloads, and regulatory reporting requirements.
Skills:
+4 years working with Data Engineering / Data Platforms / ETL pipelines;
Python and SQL for data transformation and ingestion workflows;
AWS data services (S3, Glue, Lambda, Step Functions, IAM);
Snowflake / Spark / Databricks distributed data engines;
Modelling data for analytics, reporting/AI workloads;
Large datasets, batch processing, and incremental loads;
AI / Machine Learning workloads through data pipelines, feature datasets, or analytics platforms;
Your Responsibilities:
Implement data ingestion pipelines pulling data from REST APIs, relational databases, and event-based sources into the cloud data platform;
Develop transformation jobs in Python and Spark to prepare datasets for analytics and machine learning;
Maintain and optimize Snowflake schemas, tables, and loading processes used by reporting and AI teams;
Work on orchestration workflows using AWS Glue and Step Functions to coordinate scheduled and incremental loads;
Ensure consistency, lineage, and traceability of data across multiple systems;
Support AI and machine learning workloads by preparing feature datasets using Python and Spark, building data pipelines in AWS and Snowflake used for model training, batch scoring, and analytics workloads;
Participate in the evolution of the cloud data platform architecture together with the cloud and backend teams;
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