Senior Data Engineer developing scalable data solutions on Databricks for analytics and operational workloads. Collaborating with cross - functional teams to modernize the data ecosystem.
About the role
- Data Engineering Intern working on data pipelines and infrastructure in fast-growing fintech. Collaborating with data engineers, learning best practices and developing data solutions.
Responsibilities
- Assist in building and maintaining data pipelines using Airflow to orchestrate workflows that ingest, transform, and deliver data into Snowflake and Databricks
- Support the design and implementation of data models in Snowflake that serve analytics, reporting, and ML use cases
- Help develop and maintain transformation logic using dbt, including writing models, tests, and documentation
- Contribute to data quality checks and validation processes to ensure accuracy, completeness, and timeliness of data
- Assist with infrastructure automation using Terraform to manage cloud resources in AWS
- Participate in troubleshooting data pipeline issues and investigating root causes alongside senior engineers
- Collaborate with data analysts, analytics engineers, and business stakeholders to understand requirements and contribute to technical solutions
- Help create and maintain documentation for data pipelines, data models, and infrastructure processes
- Participate in code reviews to develop best practices and learn from the team
Requirements
- A 3.0 GPA or higher
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field
- Basic understanding of SQL and comfort manipulating data
- Interest in data engineering, data infrastructure, and/or analytics engineering
- Familiarity with Python for scripting, data processing, or automation (preferred)
- Basic understanding of cloud platforms, particularly AWS, is a plus
- Strong analytical thinking and problem-solving skills — especially comfort working through ambiguity
- Good communication and collaboration skills; able to work cross-functionally with technical and non-technical teammates
- Eagerness to take ownership of your work and ask thoughtful questions
Benefits
- Internship is paid
- Hands-on experience
- Collaborative projects
- Networking opportunities
- Professional growth
- Flexible spend controls for families
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Data Engineer focused on analytics and data pipeline development for network optimisation. Collaborating with teams to deliver high - quality data solutions with Python and SQL.
Senior Product Manager defining platform capabilities for Data Cloud in Salesforce. Collaborating with R&D teams while shaping product strategy for Data 360 integration.
Senior Data Engineer at Goodwin enhancing data platforms and fostering data - driven culture across teams. Collaborating with IT and Finance on technology solutions and data governance practices.
Director, Data Platform Design and Strategy at MedImpact leading data platform and AI innovations to enhance healthcare services. Overseeing enterprise projects and managing teams to meet strategic goals.
Data Engineer delivering AI - and data - driven solutions for Honeywell’s industrial customers. Architecting and implementing scalable data pipelines and platforms focused on IoT and real - time data processing.
Data Engineering Associate focusing on data quality control and management for distribution platform. Collaborates on large scale data projects to ensure data accuracy and availability for users.
Data Architect managing enterprise data platform built on Microsoft Fabric at Johnstone Supply. Leading architectural standards and collaborating with business and IT leaders for strategic data - driven insights.
Data Engineer at Studyportals responsible for data pipelines and infrastructure. Join a team ensuring accurate and trustworthy data for analytics and business decisions.
AI/ML Engineer designing and refining prompts and workflows using large language models. Responsible for developing data pipelines and delivering scalable AI solutions in a hybrid work environment.