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 modelling.
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
Additional Role Details: 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.
Required Qualifications
5-8 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 ccelerated 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).
