<p>Summary<br>We are seeking a Data Engineer to support the development of a Data Intelligence Platform. This role focuses on data modeling, data services, data pipelines, and cloud-based data infrastructure for reporting, analytics, and data science.</p><p>General information<br>This Data Engineer will support data-related operations across a broader Data Intelligence Platform team. The work includes building and consuming web services, integrating search technologies, supporting personalization and recommendation engines, and applying data engineering best practices across the platform.</p><p>The role spans cloud-based data architecture, database performance, pipeline automation, and support for data scientists, researchers, and internal business units. The environment includes AWS-based infrastructure and a mix of structured and unstructured data sources.</p><p><strong>Tasks and Deliverables</strong><br>- Participate in the architecture design and implementation of high-performance, scalable, and optimized data solutions.<br>- Create data models from scratch using strong SQL fundamentals.<br>- Write and optimize in-application SQL statements.<br>- Ensure the performance, security, and availability of databases.<br>- Prepare documentation and technical specifications.<br>- Handle database procedures such as upgrades, backups, recovery, and migration.<br>- Profile server resource usage and optimize configurations as necessary.<br>- Design, build, and automate the deployment of data pipelines and applications.<br>- Integrate data from on-premise databases and external data sources using REST APIs and harvesting tools.<br>- Collaborate with business units and data science teams on data access, transformation, processing, and reporting needs.<br>- Support implementation, technical issues, and training related to the data lake ecosystem.<br>- Work with the team to manage AWS resources, including EMR and ECS clusters.<br>- Support provisioning, monitoring, configuration, and maintenance of AWS tools.<br>- Evaluate and promote new cloud technologies that improve capabilities and lower operating costs.<br>- Support automation efforts using Infrastructure as Code with Terraform and CI/CD tools such as Jenkins.<br>- Work with the team to implement data governance, access control, and security risk reduction.</p><p><strong>Required experience</strong><br>- 7-9 years of experience designing and developing cloud-based data models, ETL pipelines, and infrastructure.<br>- Experience working with both structured and unstructured data.<br>- Strong proficiency with SQL across popular databases.<br>- Experience optimizing large, complex SQL statements.<br>- Knowledge of best practices for relational databases.<br>- Experience configuring database engines and orchestrating clusters.<br>- Ability to plan resource requirements from high-level specifications.<br>- Ability to troubleshoot common database issues.<br>- Experience with Spark, Glue, EMR, and Apache Kafka or AWS Kinesis.<br>- Experience with version control tools such as Git or Subversion.<br>- Experience using automated build systems and CI/CD workflows.<br>- Experience programming in Java, Python, and Scala.<br>- Knowledge of data structures and algorithms.<br>- Knowledge of relational, NoSQL, graph, document, key-value, and time-series databases.<br>- Knowledge of scalable data model design and management.<br>- Knowledge of ML model deployment.<br>- Knowledge of AWS cloud platforms.<br>- Knowledge of TDD and BDD.<br>- Strong interest in improving software development skills, frameworks, and technologies.</p><p><strong>Engagement highlights</strong><br>- Opportunity to work across data modeling, data services, and data science within a broader Data Intelligence Platform.<br>- Exposure to a varied technical environment spanning AWS, ETL pipelines, databases, search technologies, and recommendation systems.<br>- Direct collaboration with data science teams and internal stakeholders on reporting, transformation, and platform capabilities.</p>