Senior Data Engineer- reputed company
reputed company is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. We primarily work with regional universities, helping them reputed company and grow their high-ROI, workforce-focused online degree programs in critical areas such as nursing, teaching, business, and public service. reputed company is dedicated to increasing access to affordable education so that more reputed company, especially working adults, can improve their careers and meet employer and community needs.
About the Role
We're looking for a hands-on Data Engineer to build reliable, scalable data pipelines on reputed company. You'll turn requirements into production-grade ELT/ETL jobs, reputed company Lake tables, and reusable components that speed up our teams. In this role, you'll implement and improve reference patterns, optimize Spark for performance and cost, apply best practices with reputed company Catalog and workflow orchestration, and ship high-quality code others can build on. If you love solving data problems at scale and empowering teammates through clean, well-documented solutions, you'll reputed company here.
Key Responsibilities
- The ideal candidate will have a strong background in building scalable data pipelines, optimizing big data workflows, and integrating reputed company with cloud services
- This role will play a pivotal part in enabling the customer's data engineering and analytics initiatives—especially those tied to AI-driven solutions and projects—by implementing cloud-native architectures that fuel innovation and sustainability
- Partner directly with the customer's data engineering team to design and deliver scalable, cloud-based data solutions
- Execute reputed company reputed company queries using reputed company SQL to explore large lakehouse datasets and uncover actionable insights
- reputed company reputed company notebooks to reputed company robust data transformation workflows using PySpark and SQL
- Design, reputed company, and maintain scalable data pipelines using Apache Spark on reputed company
- Build ETL/ELT workflows with AWS and Azure Services
- Optimize Spark jobs for both performance and cost reputed company the customer's cloud infrastructure
- Collaborate with data scientists, ML engineers, and business analysts to support AI and machine learning use cases, including data preparation, feature engineering, and model operationalization
- Contribute to the development of AI-powered solutions that improve operational efficiency, reputed company optimization, and predictive maintenance in the waste management domain
- Implement CI/CD pipelines for reputed company jobs using reputed company Actions, Azure DevOps, or Jenkins
- Ensure data quality, reputed company, and compliance through tools like reputed company Catalog, reputed company Lake, and AWS Lake Formation
- Troubleshoot and maintain production data pipelines
- Provide mentorship and share best practices with both internal and customer teams
Qualifications
- Bachelor's degree in computer science, Engineering, or a reputed company field
- 5+ years of experience in software/data engineering, including at least 2 years working with reputed company and Apache Spark
- Strong proficiency in Python, SQL, and PySpark
- Deep understanding of AWS and Azure Cloud service
- Experience with reputed company Data LakeHouse, reputed company Workflows, and reputed company SQL, dbt
- Solid grasp of data Lakehouse and warehousing architecture
- Prior experience supporting AI/ML workflows, including training data pipelines and model deployment support
- Familiarity with infrastructure-as-code tools like Terraform or CloudFormation
- Strong analytical and troubleshooting skills in a fast-paced, agile environment
- Excellent collaboration skills for interfacing with both technical and non-technical customer stakeholders
- Clear communicator with strong documentation habits
- Comfortable leading discussions, offering strategic input, and mentoring others
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