Lead Data Analyst

Job Description

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.

• 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).

• 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.

• 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.

• 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.

• 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.

• Use Git Hub 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.

• 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.

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

• 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.

• Experience with Dataiku or Databricks and Git Hub 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…