Google Data Engineer
Slalom
Join Slalom as a Google Data Engineer, focusing on scalable ETL/ELT pipelines and both batch and real-time data engineering.
Last checked on September 8, 2026. We may earn a commission when you click through.
This position is well-suited for data professionals eager to work with technologies in a collaborative environment. However, the lack of salary transparency could be a drawback for some applicants.
About this role
Join Slalom as a Google Data Engineer, focusing on scalable ETL/ELT pipelines and both batch and real-time data engineering.
About the Company
Slalom is a modern consulting firm that helps companies solve challenges through custom software and data solutions.
Key Highlights
- ✓ Focus on batch and real-time data engineering
- ✓ Build scalable ETL/ELT pipelines
- ✓ Work with modern cloud-native architectures
- ✓ Collaborate with clients to create custom solutions
💡 Honest Take: While the role offers exciting tech opportunities, be aware that project scopes can change rapidly, and client demands may lead to tight deadlines. Networking and adaptability are key to success here.
Pros
- ✓ Opportunity to work with advanced data technologies
- ✓ Collaborative work environment
- ✓ Focus on innovative solutions
Cons
- ✗ Salary not disclosed
- ✗ Potentially high client demands
- ✗ Work may require rapid adaptation to project changes
Best For: Experienced data engineers in the U.S. looking for collaborative roles that emphasize innovation and client interaction.
Watch Out: Be prepared for fluctuating project demands that may require quick adjustments in your work approach.
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What Customers Say
Workers appreciate the collaborative environment but note the high demands placed by clients.
Expert Review
The role of Google Data Engineer at Slalom emphasizes the development of scalable ETL/ELT pipelines, which is crucial for modern data workflows. Candidates can expect to engage with both batch and real-time data, appealing to those passionate about innovative engineering solutions. Slalom’s collaborative culture fosters teamwork, but the dynamic nature of client projects means that workloads can change unexpectedly.
Staying adaptable is essential to meet varying client expectations. While the position offers a great opportunity to work with advanced technologies, potential applicants should be cautious about the absence of disclosed salary information. This lack of transparency can create uncertainty regarding compensation expectations.
Overall, this role is ideal for data engineers who value work and enjoy direct client engagement. If you prefer a stable routine, this might not be the best fit for you.
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