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 Puna remote: Po Burimi: https://al.linkedin.com/jobs/view/data-scientist-at-ticketnetwork-4353461142

Niveli: mid level