Overview
On Site
Depends on Experience
Contract - W2
Contract - 12 Month(s)
No Travel Required
Skills
Collaboration
Agile
Amazon Web Services
Apache Spark
Big Data
Cloud Computing
Data Governance
Communication
Computer Science
Data Architecture
ER/Studio
Data Modeling
Data Warehouse
Google Cloud Platform
Databricks
DevOps
Extract
Transform
Load
Mentorship
Good Clinical Practice
ELT
IT Management
Information Systems
Management
Leadership
Meta-data Management
Regulatory Compliance
Microsoft Azure
Data Engineering
Stakeholder Management
Scala
Optimization
Job Details
- Lead the design and development of enterprise-level conceptual, logical, and physical data models.
- Architect and optimize data pipelines and models using Databricks, Delta Lake, and Lakehouse architecture.
- Collaborate with data engineers, analysts, and business stakeholders to translate complex requirements into robust data solutions.
- Define and enforce data modeling standards, governance, and best practices.
- Conduct performance tuning and optimization of large-scale data systems.
- Oversee metadata management and ensure data lineage and traceability.
- Provide technical leadership and mentorship to junior data modelers and engineers.
- Stay current with emerging data technologies and recommend strategic improvements.
Qualification:
- Bachelor s or Master s degree in Computer Science, Information Systems, or related field.
- 8-20 years of experience in data modeling, data architecture, and data engineering.
- Proven expertise in Databricks, Apache Spark, and SQL.
- Strong experience with cloud platforms (Azure, AWS, or Google Cloud Platform).
- Deep understanding of data warehousing, ETL/ELT processes, and big data ecosystems.
- Familiarity with Delta Lake, Unity Catalog, and Lakehouse principles.
- Excellent communication, leadership, and stakeholder management skills.
Preferred Skills:
- Experience with modeling tools like ER/Studio, PowerDesigner, or dbt.
- Proficiency in Python or Scala for data transformation.
- Knowledge of data governance frameworks and compliance standards.
- Agile and DevOps experience in data-centric environments.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.