Senior Data Engineer (Perm, Ireland, Hybrid )

<p><strong>Senior Data </strong><strong>Engineer</strong><strong> (Perm, Ireland, Hybrid)</strong></p> <p><em>This is a permanent full time opportunity for those based in Ireland. This role will require travel to Germany.</em></p> <p> </p> <p><strong>About Nearform<br></strong></p> <p>Nearform is an independent team of data & AI experts, engineers, and designers who build intelligent digital solutions and capability at pace. We create AI-enabled solutions that enhance digital experiences, empower developers, and deliver measurable results. In these ways, we partner with ambitious enterprises to deliver enduring impact.</p> <p>Our deep expertise in solving the world’s most complex digital problems, along with our collaborative, people-first approach, enables enterprises to build breakthrough products and modernise legacy systems by unleashing the power of AI.</p> <p>Today, our team of 500 experts in 20+ countries is trusted by leading enterprises including Lululemon, Puma, Sun Life, Starbucks, Travelex, Virgin Media 02, and Walmart.  </p> <p>As part of our Engineering function, you will work closely with clients to translate complex business requirements into innovative digital products. Whether you are a Senior Engineer, Tech Lead, or DevOps Engineer, you will collaborate with distributed teams, leveraging cutting-edge technologies to build secure, high-performance applications. Our Nearform engineers are known for building high quality, scalable solutions that solve real world problems.</p> <p> </p> <p><strong>About the Senior Data Engineer role</strong></p> <p>As a Senior Data Engineer at Nearform your main task will be designing, building, and maintaining scalable data platforms, pipelines, and warehouses using SQL, Python, Spark, and other relevant technologies. You will play a key role in building efficient data solutions, optimizing performance, and ensuring seamless data integration. However as you’ll likely work on a variety of projects your responsibilities may also include:</p> <ul> <li>Designing, building, and optimizing data pipelines and ETL processes for large-scale data ingestion and transformation.</li> <li>Developing and maintaining data platforms and warehousing solutions to support analytics and business intelligence needs.</li> <li>Implementing scalable data storage solutions and ensuring high availability and performance.</li> <li>Enhancing performance in data processing workflows for maximum speed and scalability.</li> <li>Collaborating with data scientists, analysts, and stakeholders to understand business needs and translate them into data engineering solutions.</li> <li>Ensuring data quality,