Join EVOTEK: North America’s Premier Digital Business Enabler As North America's premier enabler of secure digital business, we integrate cutting-edge technical expertise across data center, network, security, cloud, and communications domains. By delivering cohesive digital solutions, we help businesses drive measurable impact and accelerate their transformation. Our award-winning culture is the cornerstone of everything we do. Recognized multiple times by Inc. Magazine as a "Best Place to Work", we’re proud to create an environment where innovation and collaboration thrive. Locally, we’ve been honored by The San Diego Business Journal as a "Best Place to Work" more than seven times, and our excellence is reflected in accolades like CRN's "Solution Provider 500", "Tech Elite 250", and "Top 150 Growth Companies”. We’ve also earned a spot among CRN’s "Triple Crown” award winners. If you’re ready to be part of a team that values innovation, culture, and business impact, EVOTEK is the place for you. Role Summary The Data Center Engineer will be responsible in design, implementation, support, and migration enterprise infrastructure across on-premises, hybrid, and cloud environments. This role focuses on virtualization, containerization, and automation to deliver secure, resilient, and scalable infrastructure solutions. Responsibilities - Deliver billable professional services engagements across hybrid data center, virtualization, and cloud environments - Execute implementation, migration, upgrade, and modernization projects for enterprise clients - Deploy and support VMware, hyperconverged, storage, and Kubernetes platforms - Lead technical workstreams during project lifecycle phases (plan, design, implement, optimize, document) - Troubleshoot and resolve complex infrastructure issues across compute, storage, and data center networking domains - Develop client-facing deliverables including implementation documentation, cutover plans, validation reports, and knowledge transfer materials - Provide regular engagement status updates to project managers and client stakeholders - Ensure solutions are deployed according to scope, best practices, and performance expectations - Contribute to repeatable delivery methodologies, standards, and service offerings - Desire and commitment to achieve and maintain vendor and industry related certifications

• Design, build, and maintain production-grade data pipelines using Airflow and AWS services like Lambda, DynamoDB • Own data ingestion from internal systems and third-party integrations (e.g., Google, Bing, external APIs). • Manage data storage and movement across S3, Snowflake, Snowpipe, and DynamoDB. • Write and maintain custom Python code that runs reliably in production. • Work across dev, staging, and production environments with proper deployment and rollback practices. • Partner with analytics, data science, and product teams to design reliable, usable data models. • Review code, mentor junior engineers, and help establish best practices for data quality, reliability, and observability. • Identify and fix performance, cost, or reliability issues in existing pipelines.

• Build and maintain data pipelines for ingestion, transformation, and reporting with guidance from senior team members • Support Data Science and Business Intelligence teams with data preparation and quality assurance • Help monitor and troubleshoot data pipeline issues under supervision • Contribute to improving data quality and pipeline reliability initiatives • Learn to work with distributed systems and cloud technologies • Write clean, well-documented code following established team practices • Develop well-documented, tested data pipelines following team coding standards and best practices • Participate in code reviews and collaborative design sessions to continuously improve your technical skills • Work closely with product stakeholders to understand business requirements and translate them into technical solutions • Support data quality monitoring and help identify and resolve data issues • Contribute to team documentation and knowledge sharing initiatives • Stay curious and continuously learn new technologies and techniques

• Develop and optimize data pipelines • Build and maintain analytical, high-performance, and well-documented data models in BigQuery • Implement and manage monitoring and testing frameworks to ensure data quality and integrity • Lead the definition and enforcement of data governance policies, including organization and cataloging of data assets • Serve as a technical reference, promoting best practices in data engineering and data modeling across the team • Collaborate with business stakeholders to understand requirements and ensure data is accessible and documented