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- Tasks: Support data ingestion and transformation processes while collaborating with senior engineers.
- Company: Bechtel, a global leader in infrastructure and engineering since 1898.
- Benefits: Part-time telework, competitive rewards, and opportunities for career growth.
- Why this job: Join a dynamic team driving digital transformation and make a real impact with data.
- Qualifications: Bachelor's degree in computer science or related field; experience in data engineering.
- Other info: Diverse and inclusive workplace committed to employee growth and development.
The predicted salary is between 28800 - 43200 ÂŁ per year.
The Infrastructure AI and Data program is a cornerstone initiative designed to transform how our Global Business Unit (GBU) manages, governs, and leverages data to drive innovation and operational excellence. As we scale digital capabilities across complex engineering and delivery environments, the ability to harness data effectively is critical to enabling advanced analytics, AI‑driven insights, and seamless collaboration across diverse stakeholders. This role is primarily execution‑focused, supporting data ingestion, transformation, and quality processes under the guidance of senior data engineers and the Data Solutions Architect. The Data Engineer will help ensure data is accurate, timely, and accessible for analytics and reporting, contributing to Bechtel’s digital transformation journey while developing technical skills in modern data engineering practices.
This position is designated as part‑time telework per our global telework policy and may require at least three days of in‑person attendance per week at the assigned office or project. Weekly in‑person schedules will be determined by the individual and their supervisor, in consultation with functional or project leadership.
Major Responsibilities- Develop and maintain ETL/ELT pipelines to ingest and transform data from multiple sources into the UDP environment.
- Collaborate with data solutions architect and functional SMEs to understand data requirements and deliver solutions aligned with business needs.
- Implement data quality checks and validation routines to ensure integrity and consistency of datasets.
- Optimize data workflows for performance and scalability within Azure Databricks.
- Document processes and contribute to best practices for data engineering within the PIIM team.
- Bachelor’s degree in computer science or related field.
- Experience in data engineering or related role.
- Proficiency in SQL and experience with Python or Scala for data processing.
- Familiarity with cloud‑based data platforms (Azure preferred).
- Understanding of data modeling concepts and ETL/ELT processes.
- Ability to troubleshoot and optimize data workflows.
- Exposure to Databricks or Spark‑based environments.
- Experience with data governance tools and practices.
- Experience with JavaScript Full‑Stack development environments including MongoDB or similar NoSQL databases.
- Knowledge of version control (Git) and CI/CD for data pipelines.
- Awareness of EPC industry data structures and standards.
Junior Data Engineer employer: Bechtel Corporation
Contact Detail:
Bechtel Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Junior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to current employees at Bechtel on LinkedIn or through mutual connections. Ask them about their experiences and any tips they might have for landing the Junior Data Engineer role.
✨Tip Number 2
Prepare for the interview by brushing up on your SQL and Python skills. Be ready to discuss how you've used these tools in past projects, as well as your understanding of ETL/ELT processes. We want to see your technical chops!
✨Tip Number 3
Showcase your problem-solving skills! Be prepared to tackle some real-world data challenges during the interview. Think about how you would optimise data workflows or ensure data quality, and be ready to share your thought process.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our extraordinary team at Bechtel.
We think you need these skills to ace Junior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Junior Data Engineer role. Highlight relevant skills like SQL, Python, and any experience with data engineering. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any data projects, make sure to mention them! Whether it's a personal project or something from your studies, we want to see your hands-on experience and problem-solving skills in action.
Apply Through Our Website: Don't forget to apply through our website! It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're serious about joining our extraordinary team!
How to prepare for a job interview at Bechtel Corporation
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals, especially ETL/ELT processes and SQL. Be prepared to discuss how you've used these skills in past projects or coursework, as this will show your understanding of the role.
✨Familiarise Yourself with Azure Databricks
Since the job mentions Azure Databricks, it’s a good idea to get comfortable with it. Try to explore its features and functionalities, and be ready to explain how you would optimise data workflows using this platform.
✨Prepare for Technical Questions
Expect technical questions related to data processing, Python or Scala, and troubleshooting data workflows. Practise coding problems or scenarios that might come up during the interview to demonstrate your problem-solving skills.
✨Show Your Collaborative Spirit
This role involves working closely with senior data engineers and other stakeholders. Be ready to share examples of how you've successfully collaborated in team settings, highlighting your communication skills and ability to contribute to group projects.
