<p>We are actively seeking experienced Front End Developers to join our talent network for upcoming contract opportunities. These roles support a range of clients and focus on building responsive, user-friendly, and high-performing web applications and digital experiences.</p><p><strong>What You’ll Do</strong></p><ul><li>Develop and maintain responsive web applications using modern front-end frameworks </li><li>Translate UI/UX designs into functional, high-quality code </li><li>Collaborate with designers, back-end developers, and product teams to deliver seamless user experiences </li><li>Ensure cross-browser compatibility, performance optimization, and mobile responsiveness </li><li>Build reusable components and front-end libraries for future use </li><li>Optimize applications for speed, scalability, and accessibility (WCAG standards) </li><li>Debug and resolve front-end issues and technical bugs </li><li>Participate in code reviews and contribute to front-end best practices</li></ul><p> </p>
<p>We are seeking a highly skilled Full Stack Data Engineer who thrives in building modern, scalable data platforms from the ground up. This is an opportunity to work on a cloud-native data stack, influence architecture decisions, and deliver solutions that directly power business insights and operations.</p><p>If you enjoy owning the full lifecycle—from data ingestion to application layer—this role will be a strong fit.</p><p><br></p><p><strong>What You’ll Do</strong></p><p>You will operate as a hands-on engineer across the full data stack:</p><ul><li>Design, build, and maintain scalable ELT pipelines and workflows</li><li>Develop and optimize data models and warehouse structures in Snowflake</li><li>Build full stack data applications and backend services</li><li>Write clean, efficient Python and SQL code</li><li>Develop reusable data frameworks and components</li><li>Implement automated testing for data quality and reliability</li><li>Build and maintain CI/CD pipelines (GitHub-based)</li><li>Create reporting and visualization solutions (Power BI or similar)</li><li>Monitor production systems and troubleshoot data issues proactively</li></ul><p><strong>Tech Stack</strong></p><ul><li>Data Platform: Snowflake</li><li>Languages: Python, SQL</li><li>Cloud: AWS / Azure / GCP (environment dependent)</li><li>DevOps: GitHub, CI/CD pipelines</li><li>Visualization: Power BI (or similar BI tools)</li></ul>
<p>We are currently seeking a Data Engineer for a contract opportunity supporting a growing data and analytics organization. This role is focused on building and maintaining modern cloud-based data infrastructure, including scalable ELT pipelines, Snowflake data solutions, and automated data workflows.</p><p>This is a hands-on engineering role where you will design, develop, and support end-to-end data systems that enable reliable reporting, analytics, and business decision-making.</p><p><strong>Key Responsibilities:</strong></p><ul><li>Design, build, and maintain scalable ELT/ETL data pipelines and workflows</li><li>Develop and optimize Snowflake-based data warehouse solutions</li><li>Build and maintain data models and transformation logic to support analytics and reporting</li><li>Write efficient and high-quality Python and SQL code to support data engineering processes</li><li>Develop reusable data engineering frameworks and backend data services</li><li>Implement and maintain CI/CD pipelines using GitHub and related tooling</li><li>Build automated testing frameworks to ensure data quality and reliability</li><li>Create reporting and visualization solutions using tools such as Power BI</li><li>Monitor production data systems and resolve performance or reliability issues</li><li>Support continuous improvement of data architecture, processes, and standards</li></ul>
<ul><li>Design, develop, and optimize data pipelines using Azure Data Services (Azure Data Factory, Azure Data Lake Storage, Azure Synapse).</li><li>Build and maintain scalable ETL/ELT workflows using Databricks (Spark, PySpark, Delta Lake).</li><li>Implement and manage data orchestration and dependency management using Dagster or similar tools.</li><li>Partner with analytics, data science, and product teams to ensure reliable, high-quality data availability.</li><li>Optimize data models and storage strategies for performance, scalability, and cost efficiency.</li><li>Ensure data quality, observability, and reliability through monitoring, logging, and automated validation.</li><li>Support CI/CD pipelines and infrastructure-as-code practices for data platforms.</li><li>Enforce data security, governance, and compliance best practices within Azure.</li></ul>