Senior Data Engineer
Senior
Analytics
Azure Data Factory
Big Data
Business Intelligence
Data Analysis
Data Analytics
Data Architecture
Data Engineer
Data Engineering
Data Integration
Data Lake
Data Management
Data Pipeline
Data Platform
Data Processing
Database
Databases
Databricks
Databricks Genie
ETL
Integration
Microsoft Azure
Reporting and Analytics
SQL
Job Description
The Senior Data Engineer at Consigli Construction will design, build, and optimize the organization’s analytical data environment, focusing on pipelines, semantic models, data quality controls, and governed access. This role combines hands-on engineering with coordination of data management activities within a cloud-based lakehouse ecosystem.
Role Details
- Location: Providence, RI (onsite)
- Salary: USD 100,000 – 120,000 per year
- Experience: Minimum 5 years in data architecture, data engineering, analytics engineering, or related roles in a modern cloud environment
Responsibilities
- Contribute to the evolution of the lakehouse architecture spanning Databricks, Azure, and Fabric
- Support ingestion, transformation, and serving patterns via Databricks notebooks, Empower, and related tools
- Maintain environments, workspaces, and CI/CD patterns under guidance from senior technical leaders
- Develop and sustain subject-area models, conformed dimensions, and governed metrics used in reporting and dashboards
- Collaborate with business and project teams to standardize KPIs for cost, schedule, risk, and operational reporting
- Refactor business logic from dashboards or ad hoc SQL into governed transformations and reusable metrics
- Scale master data domains such as Project, Vendor, Budget, and People, while stewarding data definitions
- Build, maintain, and document versioned pipelines and datasets that are code-reviewed and tested
- Implement data validation, anomaly detection, monitoring, and robust error-handling procedures
- Define SLAs, monitor reliability, and execute incident response playbooks
- Identify opportunities to improve pipeline performance and processing efficiency
- Assist with data classification, masking, access controls, and privacy-by-design principles
- Partner with security and platform teams to support audits and maintain documentation
- Work with project teams and stakeholders to understand data needs and deliver reliable, well-modeled datasets
- Promote data literacy by enabling teams to access trusted analytics assets
- Provide clear documentation and guidance on data modeling, quality, and governance
Requirements
- 5+ years in data architecture, data engineering, analytics engineering, or similar roles within a modern cloud environment
- Proven experience designing data models, building ETL/ELT pipelines, and managing lakehouse or data warehouse environments
- Hands-on experience with Databricks, MS Fabric, Delta Lake, or comparable platforms
- Experience with construction or project-based analytics is a plus
Technologies
- Databricks
- Azure
- Fabric
- OneLake
- Data Factory
- Empower
- Databricks Genie
- Claude desktop
- Delta Lake
- MS Fabric
- Sage 300/CMiC (ERP)
- Workable/SagePeople (HRIS)
- Cosential/Unanet (CRM)
Key Skills
- Strong SQL and Python capabilities
- Proficiency with Azure-based tools (Data Factory, Fabric/Lakehouse, OneLake) or equivalent Databricks tooling
- Solid understanding of data lineage, cataloging, governance, data quality frameworks, and security best practices
- Experience with CLI tools and AI-assisted workflows (Claude desktop, Databricks Genie, or equivalents)
- Familiarity with enterprise systems such as Sage 300/CMiC, Workable/SagePeople, and Cosential/Unanet is advantageous
- Excellent communication skills for translating technical concepts to business teams
- Strong analytical thinking, problem-solving, and organizational abilities
- Demonstrated ability to collaborate cross-functionally and promote data best practices
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