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
A Senior Data Engineer at Consigli Construction designs, builds, and optimizes the analytical data environment, including pipelines, semantic models, data quality controls, and governed access patterns.
Responsibilities
- Contribute to the design and evolution of Consigli's lakehouse architecture using Databricks, Azure, and Fabric.
- Support ingestion, transformation, and serving patterns across Databricks notebooks, Empower, and related tooling.
- Maintain environments, workspaces, and CI/CD patterns with guidance from senior technical leaders.
- Develop and maintain subject-area models, conformed dimensions, and governed metrics used across reporting and dashboards.
- Partner with business and project teams to align and 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 pipelines and datasets that are versioned, code-reviewed, and tested.
- Implement data validation rules, anomaly detection (rule-based or ML-assisted), monitoring, and error-handling procedures.
- Define SLAs, track reliability, and execute incident response playbooks as part of the data governance program.
- Identify opportunities to improve pipeline performance and processing efficiency on an ongoing basis.
- Assist with applying data classification, masking, access controls, and privacy-by-design principles.
- Collaborate with security and platform teams to support compliance audits and maintain documentation.
- Work with project teams and business stakeholders to understand data needs and deliver reliable, well-modeled datasets.
- Promote data literacy by helping teams access and use trusted analytics assets.
- Provide clear communication, documentation, and best-practice guidance in data modeling, quality, and governance.
Requirements
- 5+ years in data architecture, data engineering, analytics engineering, or a similar development role within a modern cloud environment.
- Strong experience designing data models, building ETL or ELT pipelines, and managing lakehouse or warehouse environments.
- Experience with Databricks, MS Fabric, Delta Lake, or similar 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 their Databricks equivalents.
- Deep understanding of data lineage, cataloging, governance, data quality frameworks, and security best practices.
- Experience using CLIs and AI-assisted workflows (Claude desktop, Databricks Genie, or equivalent).
- Familiarity with enterprise systems such as Sage 300/CMiC (ERP), Workable/SagePeople (HRIS), and Cosential/Unanet (CRM) is a plus.
- Excellent communication skills, with the ability to translate complex technical concepts for business teams.
- Strong critical thinking, problem-solving, and analytical abilities.
- Proven ability to collaborate cross-functionally and promote adoption of data best practices.
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