C

Concora Credit

Platform Senior Data Engineer

Full-TimeDeadline 10/2/27
No salary listed
Senior
Beaverton, OR, USA
In Person
Data & AnalyticsData Engineering
No H1B Sponsorship

About the job

Requirements
  • At least 5 years of experience in Data Engineering, Data Platform Engineering, or a related field.
  • Strong hands-on experience with Databricks, Apache Spark, PySpark, Python, SQL, Azure Data Lake Storage, and Delta Lake.
  • Deep understanding of distributed data processing and large-scale data architectures.
  • Strong knowledge of data engineering principles, including data modeling, ETL and ELT design patterns, data quality and observability, metadata management, data lifecycle management, and Master Data Management concepts.
  • Strong understanding of modern table formats and storage architecture.
  • Experience with performance optimization techniques.
  • Experience implementing CI/CD and infrastructure automation using tools.
  • Ability to operate independently while leading initiatives in a fast-paced, agile environment.
Responsibilities
  • Design, develop, and optimize scalable data pipelines and data solutions using Databricks, PySpark, SQL, and Python.
  • Build and maintain reliable data models and ETL/ELT processes that support analytics, business intelligence, machine learning, and AI.
  • Establish and maintain data engineering standards, governance, security, and best practices across Azure and Databricks.
  • Evaluate new Databricks capabilities and recommend adoption strategies, standards, and implementation patterns.
  • Monitor, troubleshoot, and optimize data pipelines and platform performance for reliability, scalability, and cost efficiency.
  • Partner with cross-functional teams to solve complex data challenges and provide technical guidance on data architecture and engineering best practices.
  • Mentor junior engineers and contribute to a culture of technical excellence and continuous improvement.
Desired Qualifications
  • Experience with Unity Catalog, Databricks Workflows, Delta Live Tables or Spark Declarative Pipelines, Structured Streaming, Kafka, or Event Hubs.
  • Experience implementing data governance frameworks and cloud security best practices.
  • Experience with RBAC, ABAC, data classification, auditing, and compliance controls.
  • Experience supporting self-service analytics platforms and integrating Databricks with Power BI or other analytics tools.
  • Experience evaluating and adopting emerging cloud and data platform technologies.
  • Experience creating engineering standards, reference architectures, and operational best practices for enterprise data platforms.
  • Experience building and delivering internal training or enablement programs for technical platforms.

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