Employment Type: Full-Time
FSLA: Salary/Exempt
Division: Information Technology
Department: Enterprise Systems & Data
Reports to: Senior Manager, Enterprise Systems & Data
Supervisory Duties: No
Salary Range: $100,000 - $120,000
Consigli is strengthening its Data & Analytics capabilities to provide reliable, real‑time, and predictive insights to project teams and business leaders. The Senior Data Engineer supports the design, build, and optimization of our analytical data environment, including pipelines, semantic models, data quality controls, and governed access patterns. This role serves as both a hands‑on technical contributor and a coordinator of data management activities—partnering with project teams, security, and analytics stakeholders to ensure our data products are trusted, well-modeled, and ready for advanced reporting and AI use cases.
Responsibilities / Essential Functions
Data Platform & Architecture Support
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Contribute to the design and evolution of Consigli’s lakehouse architecture (Databricks, Azure, Fabric).
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Support ingestion, transformation, and serving patterns across Databricks notebooks, Empower and related tools.
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Maintain environments, workspaces, and CI/CD patterns with guidance from senior technical leaders.
Data Modeling & Semantic Layer
- Support the development and maintenance of subject-area models, conformed dimensions, and governed metrics used across reporting and dashboards.
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Partner with business and project teams to align and standardize KPIs for cost, schedule, risk, and operational reporting.
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Help refactor business logic from dashboards or ad‑hoc SQL into governed transformations and reusable metrics.
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Contribute to scaling master data domains (Project, Vendor, Budget, People, etc.) and stewarding data definitions.
Pipelines, Quality & Reliability
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Build, maintain, and document pipelines and datasets that are versioned, code-reviewed, and tested.
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Implement data validation rules, anomaly detection (rule-based or ML-assisted), monitoring, and error-handling procedures.
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Participate in defining SLAs, tracking reliability, and executing incident response playbooks.
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Continuously identify opportunities to improve pipeline performance and processing efficiency.
Governance, Security & Compliance
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Assist with applying data classification, masking, access controls, and privacy-by-design principles.
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Partner with security and platform teams to support compliance audits and maintain documentation.
Collaboration & Enablement
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Work with project teams and business stakeholders to understand data needs and deliver reliable, well-modeled datasets.
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Promote data literacy by helping teams access and use trusted analytics assets.
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Provide clear communication, documentation, and best-practice guidance in data modeling, quality, and governance.
Key Skills
Technical Skills
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Strong SQL and Python skills.
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Proficiency with Azure-based tools (Data Factory, Fabric/Lakehouse, OneLake) or Databricks equivalents.
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Deep understanding of data lineage, cataloging, governance, data quality frameworks, and security best practices.
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Experience with CLI’s and AI-assisted workflows (Claude desktop, Databricks Genie, or equivalent)
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Familiarity with enterprise systems such as Sage 300/CMiC (ERP), Workable/SagePeople (HRIS), and Cosential/Unanet (CRM) is a plus.
Professional Skills
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Excellent communication skills with the ability to translate complex technical concepts for business teams.
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Strong critical thinking, problem-solving, and analytical abilities.
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Demonstrated ability to collaborate cross-functionally and drive adoption of data best practices.
Required Experience
- 5+ years in data architecture, data engineering, analytics engineering, or a similar development role within a modern cloud environment.
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Strong experience designing data models, building ETL/ELT pipelines, and managing lakehouse or warehouse environments.
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Experience with Databricks, MS Fabric, Delta Lake, or similar platforms.
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Experience with construction or project-based analytics is a plus.
