Data Solution Architect

Design and implement end-to-end data solutions: complex ETL/ELT pipelines, batch and real-time processing, and schema optimization using cloud-native tools. Build Data Lakes and Lakehouse architectures using BigQuery (must), Snowflake, or Databricks. Develop data pipelines for ingestion, cataloging, analytics, dashboards, ML predictions, etc. Migrate and transform data from relational/NoSQL databases and DWHs. Design and deploy AI/ML solutions (NLP, speech/video recognition, fraud detection – a plus). 3+ years of experience in public cloud (GCP MUST). Strong coding skills in Python, Java, or Scala. Proven experience with batch and real-time data processing (e.g., Kafka, Pub/Sub, Spark). Hands-on experience with at least 3 of the following: Cloud-based ETL/ELT pipelines BigQuery and modern data architectures (Data Lake/Lakehouse) Cloud BI tools (Looker, QuickSight) ML model development and deployment Relational and NoSQL databases (e.g., PostgreSQL, MongoDB, BigTable) 23273 / 775