Software Engineer 3

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. 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. Requirements: 5-8 years of experience in data engineering or related roles. Bachelor&rsquos or Master&rsquos degree in Computer Science, Engineering, or a related field. Required Skills: 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, Client 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. Preferred 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. 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). #AditiConsulting # 26-04642