Technology Sales at IBM is evolving its way of working to break beyond boundaries with innovative approaches. Preferring to 'show' vs. 'tell' we're looking for graduates who want to combine their deep technical education with the people skills needed to co-create with customers, partners, and colleagues - face-to-face, on solutions to our clients' most complex business challenges. In a world where technology moves at speed, it's essential that we stay ahead of the curve to provide tailored solutions that meet our clients' needs. It's not enough for us to have the technical expertise. We need to be great with people, too. To empathize. To understand. To collaborate on technical solutions that will improve lives all over the world. Excellent onboarding and an industry leading learning culture will set you up for positive impact and success, whilst ongoing development will continually advance your career. Our sales environment is collaborative and experiential. Part of a team, you'll be surrounded by bright minds and keen co-creators - always willing to help and be helped - as you apply passion to work that will compel our clients to invest in IBM's products, services, and people. We get it. Navigating your career can be challenging. So many roles.
We are seeking an accomplished Data Integration / Lakehouse Specialist to join our Data & AI team. This professional will play a critical role in designing, architecting, proposing, and optimizing complex data integration frameworks that support our enterprise data strategy across multiple environments — including cloud, hybrid, and on-premise platforms. You will contribute to mission-critical projects focused on Big Data, Data Warehousing, Lakehouse architectures, data virtualization, query federation and Real-Time Analytics, collaborating with cross-functional teams to ensure our data ecosystem is scalable, performant, and aligned with evolving business needs.
- Experience in Solution Engineer/Pre-sales Engineer/Customer Success or similar role.
- Experience in a support, analytics, development, engineering, IT, or quality assurance (QA) organization, which includes:
- Creating or managing web-based software engineering projects with a diverse dataset.
- Managing data science and analytics projects.
- Advanced SQL and NoSQL databases such as Db2, Oracle, Netezza, Teradata, Big Query, MongoDB, Cassandra, PostgreSQL, SQL Server, Presto, Trino, Apache Pinot, Impala, Redis, etc.
- Advanced Python, creating production code in an object-oriented programming framework.
- Cloud technology as AWS, IBM Cloud, Azure.
- Datalake, Lakehouse, Hadoop, Icerberg, Delta Lake, Databricks, parquet, avro, ORC, airflow, etc
- Building of data flow components and processing systems to extract, transform, load (ETL), and integrate data from various sources eitheir scripting or through visual ETL tools.
- Building dashboards, reports and data science analytics using Cognos, Tableau, SPSS, SAS, NIFI, etc
- Expertise with enterprise cloud solutions like Platform-as-a-Service (OpenShift by Red Hat), containers, Kubernetes, and IT automation (Ansible by Red Hat)
- Competent comprehension of enterprise architecture and strategic business drivers
- Ability to manage multiple issues and projects with shifting priorities and timelines
- Outstanding written and verbal communication skills; ability to convey complex information to customers both clearly and concisely
- A Bachelor’s degree or equivalent.
- Mathematics, statistics, and problem-solving aptitude.
- Fluent oral and written communication skills in English.
- Solid presentation and communication skills.
- Ability to work as part of a team to solve technical problems in varied environments.
- Knowledge in Data Governance is a plus.
- MBA degree is a plus.