Siemens is a global leader in technology and sustainability, seeking a Data Engineering Intern to help build and optimize data solutions. The intern will collaborate with senior data engineers, data scientists, and analysts to design, develop, and maintain data pipelines and processes that drive business impact.
Responsibilities
Assist in Data Pipeline Development: Contribute to the design, development, and maintenance of ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse/data lake.
Write and Optimize SQL Queries: Develop and optimize SQL queries for data extraction, transformation, and analysis.
Develop Python Scripts: Write Python scripts to automate data-related tasks, perform data cleaning, and implement data transformations.
Support Data Quality Initiatives: Help monitor data pipelines for data quality issues, troubleshoot errors, and ensure data integrity.
Document Data Processes: Assist in creating and maintaining documentation for data pipelines, data models, and data dictionaries.
Collaborate with the Team: Work closely with senior data engineers, data scientists, and analysts to understand data requirements and deliver reliable data solutions.
Learn New Technologies: Actively participate in learning new data engineering tools and technologies, including cloud platforms, big data frameworks, and orchestration tools.
Troubleshoot Issues: Aid in identifying and resolving issues related to data processing and infrastructure.
Qualification
Required
Currently pursuing a Bachelor's in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related technical field.
Strong foundational understanding of relational databases and SQL.
Proficiency in at least one programming language, preferably Python.
Basic understanding of data warehousing concepts.
Excellent problem-solving skills and a keen eye for detail.
Strong communication and teamwork abilities.
Eagerness to learn and adapt to new technologies and challenges.
Preferred
Familiarity with cloud platforms such as AWS or Azure Cloud Platform (e.g., S3, Redshift, BigQuery, Data Factory, Glue) and Snowflake.
Exposure to data integration (ETL/ELT) development using multiple languages (e.g., Java, Scala, Python, PySpark, SparkSQL)
Experience with data orchestration tools (e.g., Apache Airflow, Prefect).
Basic knowledge of data modeling techniques.
Experience with version control systems (e.g., Git Bitbucket).
Personal projects or coursework demonstrating an interest in data engineering or data science.
Benefits
Siemens empowers customers to transform the industries that form the backbone of economies: industry, transportation, buildings and grids.
