Data Engineer

San R&D Business Solutions LLC | Full time

Fremont, United States | Posted on 10/30/2025

Visa Eligibility: H1B, GC, USC, H4 candidates can apply About the Job

We are seeking a skilled and proactive Data Engineer to join our team and contribute to the design, development, and maintenance of scalable data pipelines. In this role, you will play a key part in transforming raw data into actionable insights, supporting analytics, business intelligence, and AI/ML initiatives across the organization. You will collaborate with cross-functional teams to ensure data reliability, efficiency, and quality while driving process improvements and automation.

• Build, maintain, and optimize data pipelines and ETL/ELT workflows across cloud and on-premise environments.
• Transform data from multiple structured and unstructured sources into usable formats for analytics and reporting.
• Develop, maintain, and optimize relational and non-relational data models, schemas, and storage solutions.
• Ensure high-quality, reliable, and secure data pipelines, implementing data validation, profiling, and monitoring.
• Collaborate with data scientists, analysts, and business stakeholders to understand requirements and deliver solutions that meet business needs.
• Design and implement automation and CI/CD processes for data workflows, integrating tools like Airflow, Jenkins, or similar orchestration platforms.
• Identify opportunities to optimize performance, reduce latency, and improve operational efficiency of data pipelines.
• Document and test data solutions, ensuring accuracy, compliance, and maintainability.
• Stay current with emerging technologies, cloud platforms, and data engineering best practices.

• 8+ years of experience in data engineering, data integration, or similar roles.
• Strong experience with cloud platforms such as AWS, Azure, or GCP, including cloud-native data services.
• Hands‑on expertise in Python, SQL, Spark, Hadoop, Kafka, and ETL/ELT tools.
• Experience with both relational and No
  
  SQL databases (MySQL, Postgre
  
  SQL, Mongo
  
  DB, Cassandra, etc.).
• Proficient in building scalable, high-performance data pipelines and implementing data governance and security practices.
• Familiarity with CI/CD, automation, and containerization (Docker, Kubernetes) in data workflows.
• Strong collaboration and communication skills, capable of explaining technical concepts to both technical and non-technical stakeholders.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 8+ years of experience in data engineering with strong hands‑on skills in Python, SQL, Spark, Hadoop, Kafka, ETL/ELT tools, and cloud platforms (AWS/Azure/GCP).