Data Engineer- Machine Learning & AI Implementation
**About the Role**
Portugal Lisboa Amadora
Remote vs. Office Hybrid (Remote/Office)
Siemens Energy Unipessoal Lda.
Grid Technologies Business Unit
Product Management
Full / Part time Full-time
Experienced Professional
A Snapshot of your Day:
You will improve the availability and quality of existing data and create a high-quality architecture as a basis for the sustainable implementation of AI use cases. You will collaborate with data engineers, data scientists, central functions, and external partners to implement AI use cases. Your role also includes business trips to understand and support local processes.
**How You'll Make an Impact**
1. You work in an interdisciplinary team with data scientists and business professionals to foster a data-driven company culture approach and help implement machine learning and AI use cases.
2. You support business professionals in use case refinements to identify promising use cases with high business impact.
3. You collect, maintain, prepare, enrich, validate, and distribute data.
4. You support staff in data acquisition techniques and ensure proper data collection/storage for administrative processes and on-site.
5. You plan and create a suitable system infrastructure for applications for analysis.
6. You design and configure robust data sets and databases.
7. You maintain and develop existing data infrastructure.
8. You support the conception and provision of a system architecture.
9. You build up deep knowledge with Snowflake model.
**What You Bring**
**Must have**
1. University degree in computer or data science or related field.
2. Knowledge of snowflake SQL Scripting, Alteryx, SnapLogic.
3. Knowledge in building End – to end data pipeline.
4. Experience in data migration.
5. Intercultural communication and collaboration skills.
6. Agile mindset and organizational/planning skills with the ability to work in multiple complex projects.
7. Willingness to travel with focus on central Europe (~30%).
8. Very good English skills.
**Good to have added advantage:**
1. Ideally having a track record and/or experience in data acquisition techniques.
2. Experience in DevOps and Familiar and GitLab for CICD.
3. Experience with MS Power Automate.
4. Experience in building data ingestion pipeline using AWS, Azure data services.
5. Experience and interest in data science & data analytics.
6. Experience and interest in Machine learning & AI.
7. German language skills.
**Basic research is a key driver for innovation within Grid Technologies. We drive own innovation campaigns, collaborate with in- and external partners & directly support product development with deed & profound technological expertise.**
During this process, we create & collect a huge amount of data which we need to take a closer look at. In the upcoming years, we will further deep dive into the potentials of process digitalization, Machine Learning & generative AI. Therefore we need high quality, validated data available in the right format & structure, to further evaluate them.
**At Siemens Energy, we are more than just an energy technology company. With 96,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation.**
We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
**Lucky for us, we are not all the same. Through diversity we generate power. We run on inclusion and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character – no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.**
We offer your birthday as a holiday whenever it falls on a weekday #LI-AP1