Data Engineer II

Honeywell Aerospace•Phoenix, AZ

About The Position

As a Data Engineer II at Honeywell Aerospace, you will develop and refine data pipelines that enable accurate, efficient information flow across systems, with a focus on making critical financial data readily accessible. You will build scalable solutions for real-time data delivery and automated processing from diverse sources to endpoint solutions, collaborating with Finance stakeholders to turn business requirements into reliable, well-documented data products. The role includes developing and operating ELT/ETL pipelines, transforming data with SQL and Python in Dataiku and Databricks, and publishing Snowflake views and semantic layers to support Tableau analytics. You will also support data quality, governance, performance tuning, workflow automation, version control, CI/CD, and the modernization of manual or Excel-based processes.

Requirements

US Citizen status.
Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field, or equivalent experience.
3–5 years of professional data engineering experience, including 2+ years with Snowflake in data modeling, SQL performance, and warehouse administration.
Advanced SQL skills and practical Python skills for data processing and automation.

Nice To Haves

Hands-on experience with Dataiku flows, recipes, scenarios, and plugins, and with Databricks, Spark, Delta Lake, and Jobs.
Experience preparing datasets for Tableau, including familiarity with semantic layers, live versus extract strategies, and performance best practices.
Ability to partner with Finance/FP&A teams and translate business logic into reproducible data transformations.
Strong documentation habits, communication skills, and commitment to data quality and operational excellence.
Exposure to Azure, AWS, or GCP and data services, including experience with secrets management and resource cost optimization.
Familiarity with Snowflake Streams, Tasks, and Dynamic Tables for incremental processing and near-real-time use cases.
Experience with CI/CD tools such as GitHub Actions or Azure DevOps, pytest/unit testing, and environment promotion.
Knowledge of data governance, including cataloging, lineage, roles, and policies, and best practices for financial data controls.
Background in finance concepts such as GL, P&L, balance sheet, budgeting, and forecasting.

Responsibilities

Build and maintain ELT/ETL pipelines that ingest data from financial systems, ERP/CRM systems, files, and APIs into Snowflake, ensuring reliability, observability, and recoverability.
Develop transformations using SQL and Python in Dataiku and Databricks to create trusted, reusable finance data marts and subject-area tables.
Automate and orchestrate workflows, including scheduling, dependency management, and alerts, and implement robust logging and monitoring.
Publish performant Snowflake views and semantic layers for Tableau analytics, and optimize query patterns to support dashboard performance and scalability.
Implement data validation, reconciliations and tie-outs to source systems, lineage documentation, and access controls; uphold standards for PII and financial data.
Gather requirements and collaborate with Finance/FP&A, Accounting, and business analysts to translate business metrics into data models and pipelines.
Tune performance using Snowflake features, clustering strategies, and cost-efficient warehouse configurations.
Manage code in Git, contribute code reviews and unit/integration tests, and promote changes through development, test, and production environments.
Modernize processes by converting manual or Excel-based work into automated, auditable pipelines and prototyping Python utilities and frameworks.