Manager - Data Engineering-Data Architecture

Bristlecone•Dallas, TX

About The Position

Bristlecone Inc.’s Data Services – Delivery team seeks a senior data architect who can bridge finance expertise with modern data engineering. You will own the design of target architectures for client finance data, guiding data from ERP and sub‑ledger sources through rigorous modeling, testing, and reconciliation so the Controller’s office and FP&A can rely on accurate, timely information at month‑end close. This client‑facing role splits your time between high‑level design/review and hands‑on development using SQL, dbt, and Python.

Requirements

8+ years of data engineering or data architecture experience, with at least 5 years focused on finance data platforms.
Deep expertise in Snowflake architecture, including clustering, micro‑partitions, and role‑based security.
Advanced SQL proficiency and hands‑on experience with dbt for data transformation.
Strong Python programming skills for building ETL pipelines and automation.
Hands‑on experience extracting data from ERP systems such as Oracle, SAP, or Workday.
Solid understanding of accounting concepts, journal entries, and month‑end close processes.
Proven client‑facing consulting experience, able to communicate complex technical ideas to business audiences.
Track record of designing, documenting, and delivering end‑to‑end data solutions that meet strict accuracy and performance requirements.
Experience with data testing frameworks, CI/CD pipelines, and version control (Git).
Excellent written and verbal communication skills, with the ability to produce clear technical documentation.

Responsibilities

Design end‑to‑end finance data architectures, from ERP/sub‑ledger extraction to Snowflake warehouse delivery.
Lead data modeling, testing, and reconciliation processes to ensure month‑end reporting accuracy.
Develop and maintain Snowflake schemas, tables, and performance‑tuned queries.
Build, test, and document dbt models that translate raw finance data into trusted analytics.
Write Python ETL scripts for data ingestion, transformation, and validation.
Collaborate with Controllers, FP&A, and other finance stakeholders to capture requirements and translate them into technical designs.
Produce clear architecture diagrams, data dictionaries, and technical documentation for client teams.
Conduct client workshops and presentations to explain data flows, journal entry mappings, and warehouse configurations.
Ensure data security, governance, and compliance with industry standards.
Mentor junior engineers and promote best practices in data engineering and finance domain knowledge.