Data Engineer II

KEY RESPONSIBILITIES

• Build and maintain ELT/ETL pipelines that ingest data from varied sources (financial systems, ERP/CRM, files, APIs) into Snowflake; ensure reliability, observability, and recoverability.
• Develop transformations using SQL and Python within Dataiku (recipes, flows, scenarios) and Databricks (notebooks, Jobs, Delta Lake/Spark) to produce trusted, reusable finance data marts and subject-area tables.
• Automate and orchestrate workflows (scheduling, dependency management, alerts) in Dataiku/Databricks; implement robust logging and monitoring.
• Enable Tableau analytics by publishing performant Snowflake views and semantic layers; optimize query patterns (warehouses, micro-partitions, caching) to support dashboard performance and scalability.
• Data quality and governance: implement validation rules, reconciliations/tie-outs to source systems, lineage documentation, and access controls; uphold standards for PII and financial data.
• Requirement gathering & stakeholder collaboration: work directly with Finance/FP&A, Accounting, and business analysts to translate metrics (e.g., period close, variance analysis, forecasting) into data models and pipelines.
• Performance tuning: leverage Snowflake features (e.g., Tasks, Streams, Dynamic Tables where appropriate), clustering strategies, and cost-efficient warehouse configurations.
• Version control and CI/CD: manage code in Git, contribute reviews, unit/integration tests, and promote changes through dev/test/prod.
• Process modernization: convert manual/Excel processes into automated, auditable pipelines; prototype utilities and frameworks in Python

Qualifications

• YOU MUST HAVE
• US Citizen status
• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, or related field (or equivalent experience).
• 3–5 years of professional data engineering experience, including 2+ years with Snowflake (data modeling, SQL performance, warehouse administration).
• Advanced SQL and practical Python skills for data processing and automation.
• WE VALUE
• Hands-on experience with Dataiku (flows, recipes, scenarios, plugins) and Databricks (Spark, Delta Lake, Jobs) for pipeline development and orchestration.
• Experience preparing datasets for Tableau consumption; familiarity with semantic layers, live vs. extract strategies, and performance best practices.
• Demonstrated 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 cloud platforms (Azure, AWS, or GCP) and data services; 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 (e.g., GitHub Actions/Azure DevOps), pytest/unit testing, and environment promotion.
• Knowledge of data governance (cataloging, lineage, roles/policies) and best practices for financial data controls.
• Background in finance domain concepts (GL, P&L, balance sheet, budgeting & forecasting).
• BENEFITS OF WORKING FOR HONEYWELL AEROSPACE
• In addition to a performance-driven salary, cutting-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell Aerospace employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays.
• The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.

ABOUT US