Data Engineer II at Honeywell Aerospace in Phoenix, AZ, is responsible for building and maintaining ELT/ETL pipelines that ingest data from varied sources (financial systems, ERP/CRM, files, APIs) into Snowflake, ensuring reliability and observability. The role develops transformations using SQL and Python within Dataiku (recipes, flows, scenarios) and Databricks (notebooks, Jobs, Delta Lake/Spark) to produce trusted finance data marts and subject-area tables, and automates workflows with robust logging and monitoring. It enables Tableau analytics by publishing performant Snowflake views and semantic layers, and supports dashboard performance through optimized warehousing (warehouses, micro-partitions, caching). The position emphasizes data quality and governance, including validation rules, reconciliations/tie-outs to source systems, lineage documentation, and access controls, with adherence to PII and financial data standards. Collaboration with Finance/FP&A, Accounting, and business analysts is required to translate metrics into data models and pipelines. Additional responsibilities include performance tuning of Snowflake features (Tasks, Streams, Dynamic Tables where appropriate), clustering strategies, and cost-efficient warehouse configurations; version control and CI/CD practices; and modernizing processes by converting manual Excel workflows into automated pipelines.

Data Engineer II at Honeywell Aerospace in Phoenix, AZ, is responsible for building and maintaining ELT/ETL pipelines that ingest data from varied sources (financial systems, ERP/CRM, files, APIs) into Snowflake, ensuring reliability and observability. The role develops transformations using SQL and Python within Dataiku (recipes, flows, scenarios) and Databricks (notebooks, Jobs, Delta Lake/Spark) to produce trusted finance data marts and subject-area tables, and automates workflows with robust logging and monitoring. It enables Tableau analytics by publishing performant Snowflake views and semantic layers, and supports dashboard performance through optimized warehousing (warehouses, micro-partitions, caching). The position emphasizes data quality and governance, including validation rules, reconciliations/tie-outs to source systems, lineage documentation, and access controls, with adherence to PII and financial data standards. Collaboration with Finance/FP&A, Accounting, and business analysts is required to translate metrics into data models and pipelines. Additional responsibilities include performance tuning of Snowflake features (Tasks, Streams, Dynamic Tables where appropriate), clustering strategies, and cost-efficient warehouse configurations; version control and CI/CD practices; and modernizing processes by converting manual Excel workflows into automated pipelines.