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Data Engineer
Location
United States
Posted
95 days ago
Salary
0
Seniority
Junior
Job Description
Data Engineer
V4C ai
• Collaborate with team members and stakeholders to understand data requirements and contribute to building scalable data pipelines and workflows in Databricks. • Develop and implement ETL/ELT processes using Databricks, Python, SQL, and related tools to ingest, transform, and prepare data. • Assist in optimizing data workflows for better performance, reliability, and cost-efficiency within Databricks environments. • Support the creation and maintenance of data models, tables, and integrations in cloud platforms (Azure, AWS, or similar). • Work closely with cross-functional teams (data analysts, scientists, and engineers) to deliver clean, accessible data for analytics and reporting. • Monitor data pipelines, troubleshoot basic issues, and contribute to documentation and best practices. • Stay curious about new Databricks features and data engineering trends to support ongoing improvements.
Job Requirements
- Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
- 1-2 years of professional experience in data engineering, data processing, analytics engineering, or a closely related role (internships, co-ops, or academic projects with relevant tools count toward this).
- Hands-on experience and comfort building basic data pipelines or transformations.
- Proficiency in Python and SQL; experience with Scala is a plus but not required.
- Basic understanding of cloud platforms such as Azure, AWS, or GCP (ex: working with storage, compute, or data services).
- Solid analytical and problem-solving skills with attention to detail and a focus on writing clean, maintainable code.
- Strong communication skills and ability to work collaboratively in a remote team environment.
- Eagerness to learn, take ownership of tasks, and grow within data engineering.
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Senior Data Engineer
RohirrimThe AI-Native Platform Rewriting the Architecture of Modern Acquisitions.
• Design, build, and optimize data pipelines and infrastructure for AI products • Collaborate closely with AI/ML teams, product teams, and security/compliance partners • Develop and operate ETL/ELT workflows • Implement and optimize vector database systems and embeddings pipelines • Architect and manage Azure-based data infrastructure • Build internal tools for metadata extraction and document parsing • Monitor and improve pipeline performance and reliability
• Assist with an ongoing effort to converge legacy systems onto existing system’s Azure PaaS cloud environment. • Help architect a common data model and establish data pipelines. • Implement ETL solutions and create SQL views, stored procedures, and functions as needed. • Work with a team that follows the Scrum Agile framework. • Perform data engineering work including implementing ETL solutions and creating data architecture documentation. • Document architecture and SOPs, processes, data flows, and technical decisions for internal and client use. • Assist in designing and implementing ETL pipelines using Azure cloud tools including Data Factory and Logic Apps. • Support data ingestion from structured and unstructured sources.
