What are the responsibilities and job description for the Regulatory Data Analyst position at Heitmeyer Consulting?
Location: 100% remote – must work EST hours
Job Summary:
We are seeking a highly skilled Data Analyst to support our banking client’s Regulatory and Finance teams. This role requires strong SQL expertise, experience in data mapping and modeling, and a background in banking regulatory environments. The ideal candidate will be comfortable working independently in a remote setting and collaborating with business stakeholders to deliver high-quality data solutions.
Key Responsibilities:
Job Summary:
We are seeking a highly skilled Data Analyst to support our banking client’s Regulatory and Finance teams. This role requires strong SQL expertise, experience in data mapping and modeling, and a background in banking regulatory environments. The ideal candidate will be comfortable working independently in a remote setting and collaborating with business stakeholders to deliver high-quality data solutions.
Key Responsibilities:
- Collaborate with Line of Business (LOB) SMEs and BAs to identify and source required data.
- Create and model complex datasets for downstream consumers in Regulatory and Finance.
- Lead data mapping meetings and curate requirements for ETL development.
- Develop mapping documents including business rules, transformation logic, derived column expressions, and SQL.
- Participate in the design and testing phases depending on dataset complexity.
- Write efficient SQL queries and contribute to the development of data models and ERDs.
- Must be able to write complex SQL queries from scratch.
- Any cloud platform experience is acceptable.
- Prior experience in a regulatory function within a bank is essential.
- Proven experience leading data mapping efforts.
- Ability to contribute to data model design and interpret Entity Relationship Diagrams (ERDs).
- Strong written and verbal communication skills are a must.
- Experience with Google Cloud Platform (GCP) and BigQuery
- Familiarity with SAS and Python