STV is seeking an enthusiastic and motivated Data Engineering Intern to join our team. This internship offers an opportunity for undergraduate and graduate-level candidates to work alongside our experienced team, learn, and contribute to meaningful projects.
In this role, you will work closely with our experienced data engineering team to gain hands-on experience in designing, developing, and maintaining data pipelines and systems to support our data-driven initiatives. This internship offers an exciting opportunity to learn from industry professionals, contribute to real-world projects, and develop valuable skills in data engineering.
Responsibilities:
· Work alongside our team to develop innovative data transformation pipelines for data from a wide variety of sources.
· Collaborate with team members to advance the use of data in the industry.
· Aid in the development of applications to better display AEC data.
· Build skills in data transformation technology such as Azure Data Factory and Pyspark.
· Perform other tasks as assigned to support project goals and team objectives.
· Conduct exploratory data analysis (EDA) to uncover patterns, anomalies, and insights that inform model development.
· Create visualizations to effectively present findings and results to stakeholders.
· Stay updated on the latest technologies, tools, and techniques in the analytics domain and machine learning.
· Document analytical methodologies and coding efforts to ensure consistent knowledge transfer and reproducibility.
· Contribute insights and feedback during team meetings to support the iterative learning process.
· Perform other tasks as assigned to support project goals and team objectives.
Required Experience:
· Currently pursuing a bachelor's or master's degree in Computer Science, Data Engineering, or Software Engineering.
Preferred Qualifications:
· Hands-on experience with ETL processes and tools
· Prior activity in data projects utilizing python and database technologies .
· Basic knowledge of version control systems such as Git.
· Fundamental understanding of the ETL and ELT processes.
· Experience with Python and data libraries such as pandas and numpy.
· Familiarity with SQL and experience in querying databases for data extraction.
· Understanding of data modeling and database technology such as My-SQL, SQL server, and Mongo db.
· Demonstrated ability to communicate data modeling and transformation processes using ERD diagrams and other workflow diagrams.
This position is not eligible for sponsorship.
Compensation Range:
$47,959.00 - $54,498.00STV offers the following benefits • Health insurance, including an option with a Health Savings Account • Dental insurance • Vision insurance • Flexible Spending Accounts (Healthcare, Dependent Care and Transit and Parking where applicable) • Disability insurance • Life Insurance and Accidental Death & Dismemberment • 401(k) Plan • Retirement Counseling • Employee Assistance Program • Paid Time Off • Paid Holidays • Back-Up Dependent Care • Parental Leave • Continuing Education Program • Professional Licensure and Society Memberships
STV is committed to paying all of its employees in a fair, equitable, and transparent manner. The listed pay range is STV’s good-faith salary estimate for this position. Please note that the final salary offered for this position may be outside of this published range based on many factors, including but not limited to geography, education, experience, and/or certifications.
Not sure this role is the perfect match? We encourage you to apply if STV’s work and values resonate with you. We know great candidates don’t always meet every qualification, and research shows women and people of color are less likely to apply unless they do. At STV, we believe strong talent comes from a wide range of backgrounds, and your skills and experience may align with this or another opportunity as we continue to grow.
Skills Required
- Currently pursuing a bachelor's or master's degree in Computer Science, Data Engineering, or Software Engineering.
- Hands-on experience with ETL processes and tools.
- Prior activity in data projects utilizing Python and database technologies.
- Basic knowledge of version control systems such as Git.
- Fundamental understanding of ETL and ELT processes.
- Experience with Python and data libraries such as pandas and NumPy.
- Familiarity with SQL and querying databases for data extraction.
- Understanding of data modeling and database technologies such as MySQL, SQL Server, and MongoDB.
- Ability to communicate data modeling and transformation processes using ERD diagrams and other workflow diagrams.
STV Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about STV and has not been reviewed or approved by STV.
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Healthcare Strength — Health coverage is described as comprehensive with multiple plan options and telehealth, and is often characterized as good to above average for an engineering/consulting firm. Benefits such as company-paid life/disability and FSAs further support the overall healthcare offering.
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Retirement Support — Offerings include a 401(k) with employer contributions and a discretionary annual contribution, aligning with a benefits package portrayed as competitive. Some indications suggest additional employer contributions may occur in certain years.
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Parental & Family Support — PTO, company holidays, paid parental leave, and resources like an Employee Assistance Program and backup childcare are presented as family-supportive elements. These components are frequently cited as positives within the overall package.
STV Insights
What We Do
STV offers professional services for the infrastructure that powers our lives. We are experts in transportation systems, building design, water systems and other essential infrastructure. Harnessing national expertise to solve local challenges, STV works with public and private sector clients to make communities better – now and for the future. Our expertise includes architectural, engineering, planning, environmental, program and construction management (PM/CM) and advisory services.









