Databricks - Data Engineer (IC)

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Join us and be part of this journey towards greater opportunities and brighter futures.

We are seeking a talented and motivated Databricks Engineer to join our Analytics Technology team. In this role, you will design, develop, and optimize scalable data solutions that power business intelligence, advanced analytics, reporting, and AI-driven initiatives across the organization.

You will work closely with data engineers, analysts, architects, software developers, and business stakeholders to deliver reliable, high-quality data products that enable data-driven decision making. The ideal candidate combines strong expertise in the Databricks Lakehouse Platform, modern cloud-based data architectures, and data engineering best practices. Experience with .NET/C# development is highly desirable and will support seamless integration between enterprise applications and modern data platforms.

This is an excellent opportunity for a data professional who enjoys solving complex business challenges, building scalable solutions, and contributing to the evolution of a modern analytics ecosystem.

Key Responsibilities:

• Design, develop, and maintain scalable and efficient data pipelines using Databricks and cloud-native technologies.
• Build and optimize ETL/ELT processes for structured, semi-structured, and unstructured datasets.
• Develop robust data models, data quality frameworks, and monitoring solutions to ensure platform reliability.
• Support advanced analytics, machine learning, AI initiatives, and enterprise reporting through high-quality data products.
• Collaborate with business stakeholders and technical teams to translate requirements into scalable technical solutions.
• Troubleshoot data platform issues, identify performance bottlenecks, and implement effective resolutions.
• Contribute to CI/CD processes, automation initiatives, and infrastructure-as-code practices.
• Ensure adherence to data governance, security, compliance, and operational best practices.
• Participate in architectural discussions and drive continuous improvement across the data platform.

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent practical experience.
• Hands-on experience with Databricks and modern data engineering methodologies.
• Strong experience developing data pipelines using Python, Spark, and PySpark.
• Experience working with cloud platforms, preferably Microsoft Azure.
• Strong SQL skills and understanding of data warehousing concepts.
• Experience with source control and collaboration tools such as Git.
• Knowledge of data modeling, performance optimization, and data quality management.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent communication skills and the ability to work effectively within global teams.
• Ability to work independently with minimal supervision and translate business requirements into technical solutions.

Preferred Qualifications:

• Experience with Azure Databricks and the Microsoft data ecosystem.
• Knowledge of Delta Lake, Unity Catalog, and Lakehouse architecture principles.
• Experience with orchestration tools such as Azure Data Factory, Apache Airflow, or similar platforms.
• Understanding of DevOps practices, CI/CD pipelines, and automation frameworks.
• Experience developing APIs or backend services using .NET/C#.
• Familiarity with Power BI or similar business intelligence tools.
• Experience supporting AI, machine learning, or advanced analytics workloads.
• Knowledge of containerization technologies such as Docker and Kubernetes.

Technical Environment

Data & Analytics

• Databricks
• Azure Databricks
• PySpark
• Spark SQL
• Delta Lake
• Unity Catalog
• SQL
• Python

Cloud & Data Integration

• Microsoft Azure
• Azure Data Factory
• Azure Storage

Development & DevOps

• Git
• Azure DevOps
• CI/CD
• .NET
• C#
• REST APIs

Modern Platform Technologies

• Docker
• Kubernetes
• Power BI

What Success Looks Like:

• Delivering scalable, reliable, and high-performing data solutions that drive business insights.
• Improving data pipeline performance, quality, and operational efficiency.
• Promoting engineering best practices, automation, and governance standards.
• Building strong partnerships with analytics, engineering, and business teams.
• Contributing to the organization's long-term modern data and analytics strategy.

Why Join Us?

You will have the opportunity to work with modern cloud technologies, large-scale datasets, and cutting-edge analytics solutions in a collaborative and innovative environment. Your contributions will directly support data-driven decision making and help shape the future of our enterprise data platform.

Location:

ESP Work-at-Home

Language Requirements:

Time Type:

Full time