Data Engineer | $150k+
Role summary
Feldspar & Flint LLC is seeking a Data Engineer with 3+ years of experience to join a client focused on the mortgage industry. This role involves managing and optimizing a SQL Server data warehouse, designing and maintaining ETL pipelines using SSIS and Python, and contributing to a modern data stack with technologies like Spark, DuckDB, and Delta Lake. The Data Engineer will collaborate with business stakeholders and engineering teams to ensure reliable data pipelines, scalable architecture, and high-quality data. Responsibilities include performance tuning, data modeling, integration, reconciliation, and supporting BI semantic layers.
Feldspar & Flint LLC is a Recruiting & Staffing firm that specializes in operational strategy across core business functions.
Our client is looking for a Data Engineer with 3+ years of experience to support and evolve a mortgage-focused data platform. This role combines ownership of a SQL Server-based data warehouse with contributions to a modern, Python-driven data stack. You will work closely with business stakeholders and engineering teams to ensure reliable, high-quality data pipelines and scalable data architecture.
Key Responsibilities
- Own and optimize a SQL Server-based mortgage data warehouse, including performance tuning (queries, indexing, execution plans) and overall system reliability
- Design and maintain ETL pipelines (SSIS and API-based) to ingest and integrate data from external servicers and third-party sources
- Translate complex business requirements into scalable technical solutions, partnering closely with business stakeholders
- Manage daily and month-end data processing workflows, troubleshooting failures and ensuring consistent data availability
- Standardize, reconcile, and model data across multiple sources into analytics-ready data marts and support semantic layer development (e.g., SSAS Tabular)
- Contribute to modern data platform initiatives (Python, Spark, DuckDB, Polars, Delta Lake), including data quality frameworks, governance (metadata, lineage), documentation, and cloud-ready architecture
Required Qualifications
- 3+ years of experience in data engineering, data warehousing, or a related field
- Strong hands-on experience with
SQL Server
(T-SQL, performance tuning, indexing strategies)
- Proven experience building and maintaining
ETL pipelines
, preferably using SSIS and/or Python-based frameworks
- Solid understanding of
data modeling
(dimensional modeling, data marts, normalization vs. denormalization)
- Experience integrating data from external systems via APIs or batch ingestion
- Familiarity with
data reconciliation
and ensuring consistency across multiple data sources
- Exposure to
BI/semantic layers
such as SSAS Tabular or similar technologies
- Proficiency in
Python
and experience working with modern data tools (e.g., Spark, DuckDB, Polars, Delta Lake)
- Strong problem-solving skills with the ability to debug production data issues