AI Summary
Design and evolve a lakehouse environment on Azure using Databricks, Spark, and Delta Lake. Collaborate with analysts and stakeholders to build performant pipelines and trusted data. Mentor junior engineers and contribute to architectural discussions.
Key Highlights
Design and evolve a lakehouse environment on Azure
Collaborate with analysts and stakeholders to build performant pipelines and trusted data
Mentor junior engineers and contribute to architectural discussions
Technical Skills Required
Benefits & Perks
Salary: $120,000 - $135,000 + Bonus
Remote work
Opportunities for career growth
Good work is acknowledged
Job Description
Sr. Azure Data Engineer opportunity with rapidly growing financial corporation
If you’re looking for a remote role where your architectural decisions and hands on Azure/DataBricks Data Engineering expertise matter, your Databricks expertise is fully utilized, and data quality is treated as a first-class concern, this is a role worth exploring.
Employee testimonials:
- Great company to work for! Many opportunities to grow! Excellent management team!
- Opportunity to learn and become a better you.
- This company instills pride and passion into their workers. This company is consistently growing and allows you to grow with them.
- Co-workers are like family members, many opportunities for career growth, good work is acknowledged.
Title: Sr. Azure Data Engineer
Location: Remote
Compensation: $120,000 – $135,000 +Bonus
Responsibilities:
- This fully remote, full-time Senior Azure Data Engineer role sits at the center of a modern Azure-based data platform built on Databricks. The focus is on designing and evolving a lakehouse environment that people genuinely rely on—pipelines that are performant, data that can be trusted, and architectures that scale without constant intervention.
- You’ll spend your time working deeply with Databricks, Spark, Delta Lake, and Azure Data Lake Gen2, building systems that support advanced analytics, machine learning, and real business decision-making.
- The work goes well beyond writing pipelines. You’ll be responsible for how data is modeled, validated, governed, secured, and optimized. Performance tuning, data quality enforcement, and thoughtful design are part of the day-to-day, as is close collaboration with analysts and stakeholders who depend on clean, well-curated datasets.
- There’s a strong emphasis on automation, CI/CD, and repeatable processes, along with ownership of larger initiatives from design through delivery. You’ll also serve as a technical leader—mentoring junior engineers, setting standards, and contributing meaningfully to architectural discussions.
- This team values engineers who are comfortable working independently, can break down ambiguous problems, and take pride in delivering well-structured solutions on time. Agile practices are in place, but so is an expectation of accountability, documentation, and adherence to sound SDLC and governance principles.
- The environment is professional, collaborative, and mission-driven, with data engineering viewed as a strategic capability rather than a support function.
Qualifications
- Bachelor’s Degree or equivalent in Computer Science or related field required.
- License/Certification Databrick Data Engineer Associate required.
- License/Certification Databrick Data Engineer Professional preferred.
- License/Certification Microsoft Azure Data Engineer preferred.
- Minimum 5 years of experience as Data Engineer required.
- Minimum 5 years of experience Data Warehousing, Data Lakes and big date platforms required.
- Minimum 5 years Python experience required.
- Minimum 3 years Databricks experience required.