W2 Only (No C2C) :: Hybrid :: Senior Data Analyst / Engineer / Archinect with Strong Databricks, Power BI, PySpark & LeanIX Exp. || G.C / U.S.C

Senior Data Analyst / Engineer / Archinect with Strong Databricks, Power BI, PySpark & LeanIX Exp. || G.C / U.S.C

6+Months

Hybrid

W2 Only (No C2C)

Position Summary:
Join our Architecture Enablement team to build and operate enterprise architecture governance analytics. You will own data analysis and data quality for the LeanIX Data Lake, translate reporting needs into scalable datasets, and deliver insights through SQL, Databricks, and Power BI. This role bridges data engineering, governance, and business reporting, ensuring reliable architecture data for decision-making.

What you’ll do:
- Own day-to-day management, curation, and enhancement of datasets within the LeanIX Data Lake
- Design, build, and maintain consumable datasets for architecture governance, reporting, and analytics
- Translate business/reporting needs into technical data requirements and performant queries
- Query, analyze, and validate large datasets using SQL and Databricks (including notebooks and jobs)
- Perform data validation, reconciliation, and defect triage to ensure completeness and accuracy
- Monitor, measure, and improve data quality across LeanIX and related source/target systems
- Detect trends, anomalies, and root causes; recommend process and data quality improvements
- Build dashboards and visualizations in Power BI (and/or Databricks visualizations)
- Partner with engineering to integrate new Data Lake features and pipelines into downstream datasets
- Collaborate with LeanIX Build and Run teams to align technical capabilities with operational/reporting needs
- Establish repeatable standards for dataset lifecycle, documentation, testing, and data quality controls

Required qualifications:
- 6–9 years in data analysis, data management, or analytics engineering roles
- Advanced SQL with experience querying large/complex, semi-structured datasets
- Hands-on experience with Databricks or comparable cloud data platforms (e.g., Spark-based)
- Solid understanding of Data Lake concepts, data modeling for analytics, and data lifecycle management
- Proven experience in data validation, testing, reconciliation, and issue resolution
- Demonstrated data quality management (profiling, rules, monitoring, and remediation)
- Proficiency building BI reports/visuals in Power BI or similar tools
- Ability to translate business requirements into scalable, well-documented datasets and queries
- Strong analytical thinking, problem-solving, and stakeholder communication/collaboration skills

Preferred qualifications:
- Direct experience operating in Databricks Data Lake environments
- Experience with LeanIX or other enterprise architecture management (EAM) platforms
- Familiarity with PySpark for data wrangling and transformations in Databricks
- Exposure to data/architecture governance practices, metadata, lineage, and controls
- Experience in Agile/SDLC environments and supporting production “Run” operations (SLAs, incident mgmt.)
- Background establishing data quality frameworks, metrics, and observability

Role context:
- Embedded within Architecture Enablement / Architecture Governance
- Primary support for the LeanIX Run team; close partnership with LeanIX Build team to operationalize new features into datasets, reporting layers, and control processes

Core tech stack:
- Databricks, SQL, PySpark (preferred), Power BI
- Data Lake storage and governance concepts; exposure to EAM/LeanIX data structures