Overview
Hybrid
$50 - $60
Contract - W2
Contract - Independent
Contract - 6 Month(s)
Skills
Unity Catalog
Delta Lake
Auto loader
Pyspark
Azure cloud data architecture
ETL Piplines
role-based access control (RBAC)
MDM
FHIR services
SQL
Job Details
Must haves:
- Hands-on experience with Databricks (including Unity Catalog, Delta Lake, Auto loader and PySpark)
- Knowledge of Medallion Architecture patterns in Databricks and designing and supporting data pipelines in a Bronze/Silver/Gold (Medallion) architecture
- Experience conducting data profiling to identify structure, completeness, and data quality issues
- Experience in Azure cloud data architecture
- Extensive experience designing and managing ETL pipelines, including Change Data Capture (CDC)
- Experience implementing role-based access control (RBAC)
- Demonstrated ability to lead data platform initiatives from requirements gathering through design, development, and deployment
Description
- Seeking a highly skilled Senior Data Architect / Platform Data Engineer to support the design and implementation of a secure, scalable Integrated Data Hub (IDH) leveraging Databricks and Medallion Architecture. This role will focus on designing security, access controls, data modeling, metadata management, and high-volume data processing across bronze, silver, and gold layers. Experience with FHIR data standards at the gold layer is a strong asset.
Experience and Skill Set Requirements
Technical Knowledge 60%
- Expert knowledge of data warehouse design methodologies, including Delta Lake and Medallion Architecture, with deep understanding of Delta Lake optimizations.
- Proficient in Azure Data Lake, Delta Lake, Azure DevOps, Git, and API testing tools like Postman.
- Strong proficiency in relational databases with expertise in writing, tuning, and debugging complex SQL queries.
- Experienced in integrating and managing REST APIs for downstream systems like MDM and FHIR services.
- Skilled in designing and optimizing ETL/ELT pipelines in Databricks using PySpark, SQL, and Delta Live Tables, including implementing Change Data Capture (batch and streaming).
- Experienced in metadata-driven ingestion and transformation pipelines with Python and PySpark.
- Familiar with Unity Catalog structure and management, including configuring fine-grained permissions and workspace ACLs for secure data governance.
- Ability to lead logical and physical data modeling across lakehouse layers (Bronze, Silver, Gold) and define business and technical metadata.
- Experienced with Databricks job and all-purpose cluster configuration, optimization, and DevOps practices such as notebook versioning and environment management.
- Proficient in assessing and profiling large volumes of data to ensure data quality and support business rules.
- Able to collaborate effectively with ETL developers and business analysts to translate user stories into technical pipeline logic.
General Skills (40%)
- 5+ years in data engineering, ideally in cloud data lake environments
- Ability to translate business requirements into scalable data architectures, data models, and governance frameworks
- Able to serve as technical advisor during sprint planning and backlog grooming.
- Skilled in conducting data discovery, profiling, and quality assessments to guide architecture and modeling decisions
- Capable of conducting performance diagnostics and root cause analysis across multiple layers (DB, ETL, infrastructure)
- Strong communication skills for working with business stakeholders, developers, and executives
- Passion for mentoring, training, and establishing reusable frameworks and best practices
- Experience with agile practices, including sprints, user stories, and iterative development, especially when working in an agile data environment
- Experience grooming and assembling requirements into coherent user stories and use cases and managing the Product Backlog Items, refining them and communicate changes to project manager/Team Lead
- Analyze current and future data needs, data flows, and data governance practices to support enterprise data strategies
- Lead data discovery efforts and participate in the design of data models and data integration solutions
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.