Lead Data Analyst

As a Lead Data Analyst within the Finance Data Analytics team, you will own the design, build, and operational maturity of finance data products that turn business logic into reliable, enterprise‑grade analytics. You will convert business reports into Snowflake production views, deliver dynamic Tableau dashboards, and lead ETL/ELT solutions that unify disparate sources into trusted, auditable information for CFO and program decision‑making. You'll pair rigorous data quality with advanced analytics (predictive modeling, anomaly detection) and agentic AI workflows to accelerate insight generation across the finance cadence. You will partner closely with Finance (FP&A, Controllership, Program Finance), Integrated Supply Chain, and Order Management to translate requirements into scalable solutions-grounded in aerospace controls, security, and compliance.

YOU MUST HAVE

• 6+ years in data analytics/data engineering with Finance domain exposure (FP&A, Controllership, Program Finance).
• Advanced SQL; hands‑on Snowflake and Tableau experience building production‑grade views, models, and dashboards.
• Strong Python for data processing, automation, and statistical analysis; experience with ETL/ELT and orchestrating pipelines.
• Proven delivery of data validation, error checking, outlier analysis, and reconciliations that stand up to audit.
• Ability to translate complex business logic into scalable technical specifications and governed data products; excellent communication with Finance stakeholders.

WE VALUE

• Experience with Dataiku or Databricks and GitHub Copilot to accelerate secure development.
• Familiarity with ERP/EPM ecosystems (SAP/Oracle), master‑data harmonization, and finance data architecture.
• Prior work in SOX controls, continuous control monitoring, and audit analytics.
• Awareness of export controls (ITAR/EAR) and handling of controlled technical data; prior security clearance a plus.
• Experience optimizing Tableau performance and semantic layers.

US PERSONS REQUIREMENT

Due to U.S. export control laws, candidates must be U.S. citizen, U.S. permanent resident, or have protected status under asylum or refugee.

About us:

Join a company that''s reintroducing itself to the aviation community we''ve helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we''re launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.

Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world''s aircraft, your work here has reach that''s rare to find anywhere else.

Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we''re shaping what comes next.

Every horizon. Every mission. Every day.

Benefits:

Beyond a performance-driven salary, you''ll work alongside dedicated experts on technology that''s advancing aviation. As a Honeywell Aerospace employee, you''re eligible for a comprehensive benefits package that includes:

• Employer-subsidized medical, dental, vision and life insurance
• Short-term and long-term disability coverage
• 401(k) match, flexible spending accounts and health savings accounts
• Employee assistance program and educational assistance
• Parental leave and 12 paid holidays
• Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/

POSTING TIMELINE

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.

KEY RESPONSIBILITIES

Data Product Engineering

• Convert business reports and logic into enterprise‑grade reporting views in our cloud database. Building semantic layers and materialized views that are version‑controlled, documented, and performance‑tuned for finance workloads (variance, trend, forecast).

Business Intelligence & Visualization

• Build dynamic, actionable dashboards in Tableau-with governed metrics, drill‑throughs, scenario views, and executive summaries for Finance leaders. Establish and publish certified data sources; monitor adoption and performance.

ETL

• Use Python and SQL to combine data from disparate sources (ERP/EPM, project controls, supply chain, CRM, flat files, APIs) into reconciled, trusted datasets that reduce manual effort and increase accuracy. Normalize and harmonize master data (CoA, cost centers, profit centers) for consistency across the finance lifecycle.

Data Quality & Controls

• Lead data validation, error checking, outlier analysis, reconciliations/tie‑outs to source systems, exception dashboards, and QA frameworks that support auditability and repeatability (SOX‑ready). Embed role‑based access controls, evidence trails, and control monitoring.

Finance Domain Analytics

• Support program‑controls analytics including Earned Value Management (EVM) metrics (CPI/SPI, CV/SV), Estimates at Completion (EAC) trending, and contractual reporting (e.g., IPMDAR). Build dashboards and datasets that surface risk/opportunity and drive corrective actions with Program Finance.

AI/ML & Agentic Automation

• Use GitHub Copilot with Python to accelerate ETL, statistical modeling, and rapid analysis while maintaining secure coding and review practices; maintain reproducible notebooks and pipelines.

• Develop predictive models (forecast accuracy, anomaly detection, driver analysis) and agentic AI workflows (orchestrated assistants in Dataiku or equivalent) to automate repetitive analytics and triage root causes-aligned to responsible‑AI and governance standards.

Governance, compliance & security

• Design with SOX controls in mind (data integrity, evidence, continuous controls monitoring) and partner with Controllership/Internal Audit on automation of key reports and control testing.

Agile Delivery & Stakeholder Leadership

• Run an agile backlog of finance analytics use cases; collaborate across Finance, ISC, OM, and IT.

KEY RESPONSIBILITIES

Data Product Engineering

• Convert business reports and logic into enterprise‑grade reporting views in our cloud database. Building semantic layers and materialized views that are version‑controlled, documented, and performance‑tuned for finance workloads (variance, trend, forecast).

Business Intelligence & Visualization

• Build dynamic, actionable dashboards in Tableau-with governed metrics, drill‑throughs, scenario views, and executive summaries for Finance leaders. Establish and publish certified data sources; monitor adoption and performance.

ETL

• Use Python and SQL to combine data from disparate sources (ERP/EPM, project controls, supply chain, CRM, flat files, APIs) into reconciled, trusted datasets that reduce manual effort and increase accuracy. Normalize and harmonize master data (CoA, cost centers, profit centers) for consistency across the finance lifecycle.

Data Quality & Controls

• Lead data validation, error checking, outlier analysis, reconciliations/tie‑outs to source systems, exception dashboards, and QA frameworks that support auditability and repeatability (SOX‑ready). Embed role‑based access controls, evidence trails, and control monitoring.

Finance Domain Analytics

• Support program‑controls analytics including Earned Value Management (EVM) metrics (CPI/SPI, CV/SV), Estimates at Completion (EAC) trending, and contractual reporting (e.g., IPMDAR). Build dashboards and datasets that surface risk/opportunity and drive corrective actions with Program Finance.

AI/ML & Agentic Automation

• Use GitHub Copilot with Python to accelerate ETL, statistical modeling, and rapid analysis while maintaining secure coding and review practices; maintain reproducible notebooks and pipelines.

• Develop predictive models (forecast accuracy, anomaly detection, driver analysis) and agentic AI workflows (orchestrated assistants in Dataiku or equivalent) to automate repetitive analytics and triage root causes-aligned to responsible‑AI and governance standards.

Governance, compliance & security

• Design with SOX controls in mind (data integrity, evidence, continuous controls monitoring) and partner with Controllership/Internal Audit on automation of key reports and control testing.

Agile Delivery & Stakeholder Leadership

• Run an agile backlog of finance analytics use cases; collaborate across Finance, ISC, OM, and IT.