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Neudesic, an IBM Company

Data Engineer

Neudesic, an IBM Company, Seattle, Washington, us, 98127


About Neudesic Passion for technology drives us, but it's innovation that defines us .

From design to development and support to management, Neudesic offers decades of experience, proven frameworks and a disciplined approach to quickly deliver reliable, quality solutions that help our customers go to market faster. What sets us apart from the rest, is an amazing collection of people who live and lead with our core values. We believe that everyone should be

Passionate

about what they do,

Disciplined

to the core,

Innovative

by nature, committed to a

Team

and conduct themselves with

Integrity.

If these attributes mean something to you - we'd like to hear from you. Role Profile We are seeking skilled

Databricks Engineers

to join our Data and AI Practice. The ideal candidates will have extensive experience building scalable data pipelines and performing advanced analytics using Databricks. This role will focus on leveraging Apache Spark and Databricks to process and analyze large datasets, implement ETL workflows, and collaborate with cross-functional teams to deliver optimized data solutions. A strong background in Azure and Azure related technologies is strongly preferred. Key Responsibilities: Data Pipeline Development : Design, build, and maintain scalable ETL/ELT data pipelines using Databricks notebooks, workflows and DLT. Integrate data from various data sources such as Azure Data Lake, SQL databases, API services, and cloud storage Automate data ingestion, cleansing, transformation, and validation processes Big Data Processing & Analytics : Leverage Databricks to perform large-scale data processing and distributed computing Optimize and tune Apache Spark jobs to handle high-volume data workloads efficiently Collaborate with other data team members and analysts to develop advanced analytics and machine learning workflows Collaboration & Stakeholder Management : Work closely with business analysts, data architects, and product teams to understand business requirements and translate them into technical solutions Provide technical expertise and guidance on Databricks architecture, best practices, and troubleshooting Performance Optimization : Monitor and optimize Databricks clusters for cost and performance efficiency Troubleshoot performance bottlenecks, memory, and data storage issues in Spark applications Integration with Azure Services : Integrate Databricks with Azure Data Lake Storage, Fabric, ADF, and other Azure services for a seamless data ecosystem Set up and manage Databricks Delta Lake for managing large-scale, real-time, and batch data pipelines Data Governance & Security : Implement data governance frameworks and ensure data compliance with security best practices Manage access control, permissions, and data encryption within the Databricks environment Be familiar with Unity Catalog and how to manage it Automation & CI/CD : Design and implement automated testing and deployment workflows using Azure DevOps, Git, and Databricks APIs Build and maintain CI/CD pipelines for Databricks jobs, notebooks, and workflows Skills and Qualifications: 3+ years of hands-on experience with Databricks and Apache Spark for big data processing Experience implementing scalable data processing solutions using Apache Spark within Databricks Experience monitoring and troubleshooting performance bottlenecks, tuning Databricks clusters for optimal performance and best practices of Databricks implementations Extensive experience in Databricks Development & Engineering to include pipeline development, orchestration, design and optimization of notebooks and workflows in Databricks to support ETL (Extract, Transform, Load) operations Strong proficiency in Python, SQL, and Scala for data engineering tasks Experience with Azure services, particularly Azure Data Lake Storage, Fabric, Azure Data Factory, and Azure Blob Storage Experience with Spark performance tuning and optimization Excellent communication skills and ability to collaborate with cross-functional teams Preferred Qualifications: Experience with other big data technologies like Hadoop, Kafka, or HBase Familiarity with Azure Data Factory Experience with machine learning workflows in Databricks, including MLFlow Strong knowledge of SQL and relational database management systems Proficiency in programming languages such as Python, SQL, R, and Scala Experience with Azure cloud services (Databricks on Azure preferred) Experience with other Azure technologies such as Azure Data Factory, Azure Data Lake, Synapse, Fabric, Copilot, PowerBI, Azure Machine Learning, CosmosDB, Azure SQL Database, Azure Blob Storage, Azure Kubernetes Service, Azure Logic Apps, etc. Experience with Unity Catalog and MDM solutions such as Profisee Strong analytical and problem-solving skills, with a focus on performance optimization Excellent communication skills, both written and verbal, with the ability to articulate technical concepts to non-technical stakeholders Ability to work closely with cross-functional teams including business analysts, data architects, and business leaders to gather requirements and translate them into technical solutions Certifications in Databricks and Azure Business Skills Analytic Problem-Solving: Approaching high-level challenges with a clear eye on what is important; employing the right approach/methods to make the maximum use of time Effective Communication: Detailing your techniques and discoveries to technical and non-technical audiences in a language they can understand Intellectual Curiosity: Exploring new territories and finding creative and unusual ways to solve problems Data Analysis Knowledge: Understanding how data is collected, analyzed and utilized Ability to travel up to 25% For Washington, the expected base salary range for this position is between $110,000 and $165,000. The salary range may be different if the successful employee is in a different state. This position is also eligible for performance bonuses. The actual compensation will be determined based on experience and other factors permitted by law. Accommodations currently remain in effect for Neudesic employees to work remotely, provided that remote work is consistent with the work patterns and requirements of their team's management and client obligations. Subject to business needs, employees may be required to perform work or attend meetings on-site at a client or Neudesic location. Phishing Scam Notice Please be aware of phishing scams involving fraudulent career recruiting and fictitious job postings; visit our Phishing Scams page to learn more. Neudesic is an Equal Employment Opportunity Employer: All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Neudesic is an IBM subsidiary which has been acquired by IBM and will be integrated into the IBM organization. Neudesic will be the hiring entity. By proceeding with this application, you understand that Neudesic will share your personal information with other IBM companies involved in your recruitment process, wherever these are located. More Information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here: