Data Engineer - AWS Job
Yash Technologies India
IT Services and IT Consulting · 5,001-10,000 employees
About the role
Design, develop, and maintain scalable data pipelines on AWS while optimizing data warehousing solutions using Snowflake. Collaborate with cross-functional teams to integrate vector databases with AI workflows and ensure data quality and security.
What they look for
Requirements
Requires 3-5 years of experience in data engineering with strong proficiency in Python, SQL, and AWS cloud services. Candidates must have deep knowledge of Snowflake architecture and experience with graph or vector database technologies.
Benefits
Full description
YASH Technologies is a leading technology integrator specializing in helping clients reimagine operating models, enhance competitiveness, optimize costs, foster exceptional stakeholder experiences, and drive business transformation.
At YASH, we’re a cluster of the brightest stars working with cutting-edge technologies. Our purpose is anchored in a single truth – bringing real positive changes in an increasingly virtual world and it drives us beyond generational gaps and disruptions of the future.
We are looking forward to hire AWS Professionals in the following areas :
Job description:
Experience required: 3-5 years
Requirements :
Job Summary
We are looking for a highly motivated and experienced Data Engineer to join our data engineering team. The ideal candidate will have a strong background in building scalable data pipelines using the AWS cloud stack and extensive hands-on experience with Snowflake. Proficiency in Python and SQL, along with graph and vector database technologies, is essential. This role requires strong problem-solving abilities and a proactive mindset to deliver efficient, scalable, and reliable data solutions.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines on AWS using services such as S3, Glue, Lambda, Redshift, and EMR.
- Build and optimize data warehousing solutions using Snowflake, including performance tuning and data modeling.
- Write efficient and reusable code in Python and SQL for data transformation and processing.
- Collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand data requirements.
- Integrate vector databases with LLM-based applications and AI workflows.
- Monitor, troubleshoot, and improve pipeline performance and reliability.
- Ensure data quality, integrity, and security across all stages of the pipeline.
- Participate in code reviews, architecture discussions, and continuous improvement initiatives.
Required Qualifications
- 3-5 years of experience in data engineering or related roles.
- Strong hands-on experience with AWS cloud services, including data and AI workloads.
- Deep understanding of Snowflake architecture, performance tuning, and best practices.
- Advanced proficiency in Python and SQL for data pipelines, transformations, and services.
- Hands-on experience with graph databases (e.g., Neo4j, Neptune) and vector databases (e.g., Milvus, Amazon OpenSearch).
- Experience with version control systems (e.g., Git) and Git workflows.
- Experience working with Azure DevOps (AzDO) boards for backlog management in Agile environments.
- Excellent analytical and problem-solving skills.
- Strong communication and collaboration abilities.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Nice to Have skills
- Knowledge of the NVIDIA ecosystem and its applications in data and AI.
- Exposure to RAPIDS libraries (cuDF, cuML, cuGraph) or CUDA-based tooling for GPU-accelerated data processing, enabling faster transformation and optimization during large-scale ingestion workflows.
Preferred Qualifications
- Experience with orchestration tools such as AWS Step Functions.
- Familiarity with data governance and compliance practices.
- Exposure to real-time data processing frameworks (e.g., Kafka, Spark Streaming).
At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.
Our Hyperlearning workplace is grounded upon four principles
- Flexible work arrangements, Free spirit, and emotional positivity
- Agile self-determination, trust, transparency, and open collaboration
- All Support needed for the realization of business goals,
- Stable employment with a great atmosphere and ethical corporate culture
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