Join a global team focused on building reliable, scalable data solutions that support business intelligence and operational decision-making. In this senior role, you will design, develop, and maintain complex data pipelines across on-premises and cloud environments, ensuring data is accurate, accessible, and ready for use. You will translate business requirements into technical solutions that power reporting, analytics, and advanced data science initiatives. Working with SQL, Informatica, and diverse data technologies, you will contribute to data architecture, integration, and governance practices across multiple projects. You will collaborate with cross-functional stakeholders, manage complex technical dependencies, and help establish consistent data standards. This opportunity also offers the chance to share your expertise, mentor junior colleagues, and contribute to a diverse, international environment that values innovation and continuous development.
Data Engineering and Pipeline Development: Design, develop, and maintain scalable data pipelines for batch and streaming workloads, supporting both on-premises infrastructure and cloud environments.
SQL and Informatica Solutions: Build and optimize data integration workflows, transformations, and data processing solutions using SQL, Informatica, and other relevant technologies to meet business requirements.
Data Modeling and Architecture: Develop advanced data models, reusable data components, and data flows to support dimensional modeling, reporting, dashboard development, data feeds, and data science initiatives.
Business Requirements Translation: Collaborate with business and technical stakeholders to understand analytical needs, translate requirements into technical specifications, estimate workloads, and break down deliverables into manageable tasks and sprint plans.
Data Integration and API Development: Build and enhance API integrations to support increasing data volumes, greater complexity, and connectivity across enterprise systems and platforms.
Data Quality and Transformation: Prepare, cleanse, validate, and transform structured and unstructured data to ensure accuracy, consistency, and readiness for downstream analytics, reporting, and AI/ML applications.
Data Governance and Compliance: Apply data governance principles, established architectural standards, and code management practices to maintain secure, consistent, and well-managed data assets.
Reporting and Analytics Enablement: Deliver reliable datasets and access methods that support business users, reporting and visualization specialists, and data scientists in producing actionable insights.
Project Planning and Delivery: Independently manage data engineering projects of varying complexity, coordinate dependencies across teams, develop project plans, and deliver solutions within agreed timelines.
Technical Collaboration and Mentoring: Work with cross-functional teams to resolve technical challenges, contribute to architectural decisions, and provide guidance and support to junior associates when needed.
Continuous Improvement: Identify opportunities to improve pipeline performance, data reliability, integration processes, and the overall efficiency of data engineering practices.