Senior Data Engineer
LTM
Seeking a Senior Data Engineer with 3-5 years of experience in Python, Scala, and Spark SQL to build scalable big data solutions.
Last checked on September 8, 2026. We may earn a commission when you click through.
This role is ideal for experienced data professionals who thrive in collaborative environments and want to deepen their expertise in big data technologies. However, the onsite nature may limit flexibility for some applicants.
About this role
Seeking a Senior Data Engineer with 3-5 years of experience in Python, Scala, and Spark SQL to build scalable big data solutions.
About the Company
LTM is focused on delivering innovative data solutions and is committed to helping businesses leverage their data effectively.
Key Highlights
- ✓ 3-5 years of experience required in relevant technologies
- ✓ Expertise in Python, Scala, and Spark SQL
- ✓ Focus on designing scalable big data processing solutions
- ✓ Opportunity to work within Databricks ecosystem
💡 Honest Take: While this position offers a chance to work with technologies, the onsite requirement may deter some candidates. the lack of salary disclosure makes it hard to gauge overall compensation competitiveness.
Pros
- ✓ Engagement with advanced technologies
- ✓ Opportunities for professional growth
- ✓ Collaborative work environment
Cons
- ✗ No remote work options available
- ✗ Salary not disclosed
- ✗ Onsite requirement may limit applicant pool
Best For: Mid-level professionals in data engineering who prefer working onsite and are well-versed in Python and Scala.
Watch Out: The position is strictly onsite, so be prepared for a daily commute to Tampa.
You'll be redirected to talent.com
Expert Review
This role demands a solid foundation in big data technologies, specifically within the Databricks ecosystem. Candidates should be ready to tackle complex data challenges, optimizing solutions for scalability. The emphasis on onsite work can be a drawback for those seeking remote flexibility.
Our team found that the lack of salary transparency could lead to uncertainty during negotiations. Potential applicants may want to inquire about compensation during the interview process to ensure expectations align. It's crucial for candidates to weigh the onsite requirement against their personal work preferences.
In the competitive landscape of data engineering roles, this position offers a chance to work with advanced tools but may not suit everyone, particularly those who prefer remote work arrangements. Keep this in mind before applying, as the company culture is likely geared towards in-person collaboration.
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