Platform Sr. Data Engineer
- Compensation
- Not disclosed
- Location
- Beaverton, OR, US
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 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, Master Data Manag
- Strong understanding of modern table formats and storage architecture.
- Experience with performance optimization techniques.
- Experience implementing CI/CD and infrastructure automation using tools.
- Excellent problem-solving, analytical, and communication skills.
- Ability to operate independently while leading initiatives in a fast-paced, agile environment.
- Passion for building scalable, maintainable, and well-governed data platforms
Nice to have
- Experience with Unity Catalog, Databricks Workflows, Delta Live Tables / 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.
Full description
Overview
As our Platform Sr. Data Engineer, you’ll help drive Concora Credit’s Mission to enable customers to Do More with Credit – every single day.The impact you’ll have at Concora Credit:
We are seeking a Platform Senior Data Engineer with deep expertise in Azure, Databricks, Python, SQL, and distributed data systems to help drive the evolution of our enterprise data platform. This role goes beyond traditional data engineering, focusing on building and governing scalable data solutions that enable analytics, machine learning, AI, and Business Intelligence across the organization.
You will serve as a technical leader responsible for data platform governance, feature enablement, and engineering best practices while partnering closely with teams across the enterprise to ensure our data ecosystem remains secure, scalable, cost-efficient, and easy to use.
As a company grounded in innovation and entrepreneurship, we're looking for someone who enjoys solving complex technical challenges, shaping platform strategies, and enabling others' success through scalable data solutions and thoughtful governance.
We hire people, not positions. That's because, at Concora Credit, we put people first, including our customers, partners, and Team Members. Concora Credit is guided by a single purpose: to help non-prime customers do more with credit. Today, we have helped millions of customers access credit. Our industry leadership, resilience, and willingness to adapt ensure we can help our partners responsibly say yes to millions more. As a company grounded in entrepreneurship, we're looking to expand our team and are looking for people who foster innovation, strive to make an impact, and want to Do More! We’re an established company with over 20 years of experience, but now we’re taking things to the next level. We're seeking someone who wants to impact the business and play a pivotal role in leading the charge for change.
Responsibilities
As our Platform Sr. Data Engineer, you will:
- Help design, develop, and optimize scalable data pipelines and data solutions using Databricks, PySpark, SQL, and Python.
- Help build and maintain reliable data models and ETL/ELT processes that support analytics, business intelligence, machine learning, and AI.
- Help 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.