Data Architect
PalTech
full-time
Required skills
- Airflow
- AWS
- Azure
- BigQuery
- compliance
- Databricks
- end-to-end
- ETL
- GCP
- Kafka
- Snowflake
- Spark
About the role
PalTech
Website:
pal.tech
Job details:
Key Responsibilities
- Design and implement end-to-end Lakehouse and Mesh architectures using Snowflake, Databricks, or Google BigQuery.
- Lead the migration of complex legacy systems into scalable cloud-native environments, focusing on reducing "analytics friction" (a core PalTech service goal).
- Build resilient, automated ETL/ELT pipelines that handle massive volumes while maintaining sub-second latency for real-time reporting.
- Implement automated quality gates (using tools like Dataplex) and ensure end-to-end data lineage that is "audit-ready" for regulated industries like Healthcare and BFSI.
- Ensure data foundations are optimized for Generative AI and predictive modeling, enabling features like natural language querying for business users.
Technical Stack & Requirements
- Expert knowledge of AWS, Azure, or GCP data ecosystems.
- Proven mastery of Snowflake or Databricks. (PalTech is a proud Snowflake and AWS Consulting Partner).
- Deep experience with dbt, Airflow, Kafka, and Spark.
- Hands-on experience with Master Data Management (MDM) and data privacy compliance (GDPR/HIPAA).
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