About the Tech Team Technology powers everything we do at Dialectica – from communicating with clients and finding the most relevant expert profiles in just a few minutes to indexing and categorizing thousands of pieces of information every day. To do so, we have built our own proprietary web application that automates and optimizes the delivery of our market leading services. To date, the team consists of 70+ people across Software Engineering, Product & Design, TechOps, and is expected to grow further in 2024. Being part of Dialectica’s Technology Team you will have the opportunity to help build tech products according to the requirements of our internal and external clients and share the company’s vision to roll out more information services software products in the future. About the role We are seeking a Data Engineer who will contribute to organizing and managing multiple data sources. The successful candidate will primarily be responsible for designing and optimizing data pipelines that enhance data accessibility and integrity. This role involves collaborating closely with other teams such as Data Science, BI, and product development teams, that utilize or enrich data. Often there are multi-stage enrichments of data where one team's output must be effectively captured and re-made accessible for subsequent utilization by other teams. As a Data Engineer in Dialectica you will: - Create and maintain effective data pipeline architectures - Assemble large, complex data sets Design and implement infrastructure that enables teams to become more self-served - Design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. - Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies - Build and/or configure monitoring tools and alerts that assure the integrity of operations - Work with stakeholders including the Product, Engineering and Design teams to assist with data-related technical issues and support their data infrastructure needs.