The Team You Will Be Joining
- A confidential, fast-growing financial services company that is redefining the digital collections space.
- Privately held and led by a mission-driven leadership team, the company partners with financial services clients to drive effective recovery outcomes through omnichannel, AI-powered engagement.
- The organization is building out a new Charlotte hub and scaling its operations team to support continued expansion across clients and product offerings.
What They Offer You
- A hybrid role based in Charlotte, NC with meaningful visibility across leadership, strategy, and product teams
- Fast-paced, collaborative culture that values ownership, speed, and innovation
- Ability to directly impact outcomes for nationally recognized financial services clients
- Competitive compensation, benefits, and the chance to leave a lasting mark on a scaling business
Location
- Hybrid flexibility in Charlotte NC
Why This Role Is Important
- Design, build, and maintain scalable ETL/data pipelines
- Model and transform data within Snowflake, ensuring performance and security for analytics and reporting.
- Work alongside analytics and marketing teams to ingest and prepare data for AI/ML-based collections optimization.
- Write and optimize complex SQL queries, stored procedures, views, and performance-tuned table structures.
- Implement data quality, validation, and monitoring frameworks across pipelines.
- Automate operational workflows (e.g., incremental/delta loads, anomaly detection)
- Troubleshoot and resolve production data issues to ensure high availability and pipeline reliability.
- Document data flows, schemas, and system architectures.
- Stay current on industry best practices in AWS, data pipeline engineering, Snowflake, and ETL methodologies.
The Background That Fits
- 5+ years professional experience in data engineering or related field.
- Hands-on experience in building ETL/data pipelines
- Strong design & query skills in SQL for relational, analytical, and performance-optimized databases.
- Experience with Snowflake (or equivalent cloud data warehouse).
- Familiarity with data modeling (star/snowflake schemas, fact/dimension tables).
- Experience with AWS (strongly preferred)
- Solid understanding of data warehousing principles and best practices.
- Excellent problem-solving, organization, and communication skills.
- Experience working in fast-paced/adaptive startup environments.
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