Data Scientist

RCN Capital is hiring a Data Engineer (BI) to help us migrate from on-prem SQL Server and Python-based ETL to a cloud-native analytics platform. You will design and operate reliable, secure, and cost-aware data pipelines across both Microsoft Fabric and classic Azure services, then shape dimensional models that feed high-quality Power BI semantic models and reports.

In this hybrid role, you’ll lead upstream data engineering (ingestion, transformation, orchestration, quality, lineage) while also covering downstream BI needs in a small cross-functional team (DAX optimization, semantic modeling, and paginated reports). You’ll apply ETL and incremental CDC patterns, recommend the right service (Fabric Data Factory pipelines, Dataflows Gen2, Fabric Lakehouse/Warehouse, Azure Data Factory, Azure SQL/Synapse, ADLS Gen2, Databricks as needed), and partner with DevOps on Git and CI/CD.

Our domain is private/bridge lending and mortgage operations (retail, brokerage, correspondent, and table funding). Your work will directly support underwriting, funding, servicing, and executive reporting by delivering trustworthy, governed data products.

**Main Responsibilities:**

- Build and operate cloud-native data pipelines using ETL and incremental CDC patterns across Microsoft Fabric and Azure:

– Fabric: Data Factory (pipelines), Dataflows Gen2, Lakehouse (Delta tables), Warehouse, Notebooks

– Azure: Data Factory, Data Lake Storage Gen2, Azure SQL/Synapse; Databricks/PySpark when appropriate

- Design dimensional models (star/snowflake) that serve curated tables and views for analytics; document business logic and grain.

- Develop high-quality Power BI assets:

– Create/maintain semantic models, optimize DAX, and implement Direct Lake/Import as appropriate

– Build/maintain paginated reports for operational/financial use cases

- Implement robust data quality and validation (unit tests, reconciliation checks, SLAs), and track data freshness/lineage.

- Orchestrate and monitor pipelines (scheduling, alerting, retries), tune performance, and optimize cost (compute/storage).

- Engineer secure connectivity and configuration (Key Vault secrets, RBAC, Private Link where required).

- Use Git for version control; contribute to CI/CD pipelines in collaboration with DevOps (branching, PRs, release standards).

- Partner with stakeholders (Accounting, Treasury, Underwriting, Sales) to translate domain requirements into reliable data sets.

- Maintain runbooks, architecture diagrams, and data dictionaries; contribute to catalog/lineage with Purview (or Fabric equivalents).

- Evaluate and recommend patterns/services (Fabric vs Azure) that balance performance, cost, and maintainability.

**Required skills:**

- Strong SQL (T-SQL) and Python; comfortable with ETL and CDC patterns

- Hands-on with either Microsoft Fabric or classic Azure data services; ideally both:

– Fabric: Data Factory pipelines, Dataflows Gen2, Lakehouse/Warehouse, Notebooks

– Azure: Data Factory, ADLS Gen2, Azure SQL/Synapse; Databricks/PySpark a plus

- Dimensional modeling (star/snowflake); semantic modeling for Power BI

- Power BI: model design, DAX optimization, dataset performance (Direct Lake/Import), and paginated reports

- Git proficiency; familiarity with CI/CD workflows (Azure DevOps or GitHub)

- Solid grasp of security-by-design (Key Vault, RBAC), reliability (monitoring/alerting), and cost awareness.

**Required skills:**

- 3–6 years in data engineering/BI roles, delivering production-grade pipelines and models

- Proven track record building curated datasets and Power BI models for finance/operations teams

- Experience migrating or greenfield-building in cloud data platforms

Working hours: Monday - Friday, 8:00am - 5:00pm EST