Partner with Accounting and FP&A to support month-end and quarter-end close, building the datasets, reconciliations and reporting that let us close the books accurately and on time.
Design and own the architecture of curated, well-documented source-of-truth financial datasets in Snowflake/Databricks that are correct, consistent and tie out to the general ledger.
Build and own scalable batch (and where needed, near-real-time) pipelines orchestrated with Airflow/dbt, including dependency management, backfills and runbooks.
Define reusable data quality and reconciliation frameworks (tests, monitoring, alerting, SLAs) and agree with Accounting on what "done" means for financial correctness.
Drive data contracts with upstream engineering teams, mentor Analytics Engineers, and build abstractions (Python packages, UDFs, LLM-assisted tools) that make finance data users more efficient.
