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Manager - Data Engineering-Data Architecture

Bristlecone
Dallas, USA
Manager · 8+ years experience
Onsite
Discovered 1 weeks ago
dbtgitpythonsapsnowflakesql

Full Job Posting

Qualifications

  • 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.

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