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Tech Stack
Tools & technologiesApacheAWSAzureCloudETLGoogle Cloud PlatformSparkUnity
About the role
Key responsibilities & impact- Design, develop, and maintain robust and scalable data pipelines using Apache Spark and cloud-native data services.
- Build, optimize, and support ETL/ELT workflows to enable analytics, reporting, and downstream applications.
- Implement and manage data solutions using Databricks, Delta Lake, and Unity Catalog.
- Ensure data quality, reliability, and performance across large-scale and complex datasets.
- Collaborate with cross-functional teams to gather data requirements and translate them into effective technical solutions.
- Apply data engineering best practices related to scalability, security, monitoring, and maintainability.
- Support the continuous improvement of data architecture, pipeline performance, and operational stability in a cloud environment.
Requirements
What you’ll need- 7+ years of experience in data engineering or a related technical role.
- Strong hands-on experience with Databricks and Apache Spark are required.
- Experience working with Delta Lake and Unity Catalog for data management and governance.
- Solid understanding of data pipeline design, ETL/ELT patterns, and data modeling concepts.
- Experience working with cloud data platforms such as Azure, AWS, or GCP.
- Proven ability to design scalable, reliable, and high-performing data solutions.
- Strong problem-solving skills and the ability to work effectively in collaborative, fast-paced environments.
Benefits
Comp & perks- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdata pipeline designETLELTdata modelingdata qualitydata reliabilitydata performancescalabilitysecurity
Soft Skills
problem-solvingcollaborationcommunicationadaptabilityteamwork
