Senior Data Engineer – AI, AWS

🕒 May 30

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Blend360

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🤖 Artificial Intelligence

🏢 Enterprise

💰 $100M Private Equity Round on 2022-08

Artificial Intelligence • Enterprise • Consulting

Blend360 is a professional services company specializing in AI, data analytics, and data-driven solutions. They work with Fortune 1000 and large enterprise brands to tackle significant challenges by integrating people and artificial intelligence. Blend360 focuses on several domains including business intelligence, data engineering, data science, MLOps, and data governance. Their industries of expertise encompass financial services, energy, healthcare and life sciences, retail, technology, media & telecom, and travel & hospitality. Blend360 is recognized for their AI and data solutions, having earned accolades such as "AI-Enabling Solution of the Year" and being listed among the "Top Generative AI Service Providers 2024.

📋 Description

• Build and maintain the data infrastructure that supports the company’s and clients’ analytical products, ML models, and GenAI solutions • Design and implement high-scale batch and real-time data ingestion and transformation pipelines • Build and maintain lakehouse architectures using AWS S3, Glue, Redshift, and Apache Iceberg • Develop and orchestrate ML/AI pipelines using AWS SageMaker and Apache Airflow • Implement real-time streaming solutions with Apache Kafka and/or AWS Kinesis • Explore and apply GenAI patterns via AWS Bedrock, including RAG pipelines, embedding workflows, and integration with LLMs • Apply Data Mesh practices to decentralize data domains and improve team autonomy • Ensure data quality, lineage, and governance using dbt and AWS Glue Data Catalog • Optimize cost and query performance in Redshift and Athena environments

🎯 Requirements

• 5+ years of experience as a Data Engineer with a focus on cloud • Strong proficiency in Python, PySpark, and SQL for large-scale data processing and transformation • Solid experience with AWS: S3, Glue, Redshift, Athena, Lambda, SageMaker, and Kinesis • Experience orchestrating pipelines using Apache Airflow • Knowledge of data streaming with Apache Kafka or AWS Kinesis • Familiarity with dbt for data transformation and documentation • Experience with Infrastructure as Code using Terraform for provisioning data infrastructure • Knowledge of Apache Iceberg for table management in data lakes • Demonstrated interest in AI/ML — experience with ML or GenAI pipelines is a strong plus • AWS Certified Data Analytics – Specialty or AWS Certified Machine Learning (preferred)

🏖️ Benefits

• Remote work available