Architect - Data Engineering

• Big Data Platforms (Apache Spark, Presto, Amazon EMR)
• Cloud Data Warehouses (Amazon Redshift, Snowflake, Google BigQuery)
• Object Oriented Coding (Java, Python)
• NoSQL Databases (DynamoDB, Cosmos DB, MongoDB)
• Container Management Systems (Kubernetes, Amazon ECS)
• Artificial Intelligence / Machine Learning (Amazon Sagemaker, Azure ML Studio)
• Streaming Data Ingestion and Analytics (Amazon Kinesis, Apache Kafka)
• Visual Analytics (Tableau, PowerBI)
• Modern Data Workflows (Apache Airflow, dbt, Dagster)

What Youll Do

Slalom Builds Data Engineering capability is comprised of passionate, flexible technologists who love to practice and hone their craft. As tools evolve and technologies emerge, we work to stay in front of innovations in data platform development and delivery. As an Architect for Slalom Build, you will work in small, collaborative teams with minimal oversight and direction to design and deliver innovative solutions on Amazon Web Services, Microsoft Azure, and Google Cloud Platform using core cloud data warehouse tools, distributed processing engines, event streaming platforms, and other modern data technologies. In addition to building the next generation of data platforms, you will be working with some of the most forward-thinking organizations in data and analytics.

Slalom Builds Data Engineering capability is focused on injecting intelligence into products, engineering systems that support learning and insight and creating innovative data products. Within Data

Engineering we help customers build world-class products through effective use of:

Data Engineering consisting of streaming / real-time data solutions, modern data platforms and

data systems within products (i.e., database systems, graph databases, key-value stores,

document databases and transactional systems)

Data Visualization

Machine Learning and Artificial Intelligence

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• Big Data Platforms (Apache Spark, Presto, Amazon EMR)
• Cloud Data Warehouses (Amazon Redshift, Snowflake, Google BigQuery)
• Object Oriented Coding (Java, Python)
• NoSQL Databases (DynamoDB, Cosmos DB, MongoDB)
• Container Management Systems (Kubernetes, Amazon ECS)
• Artificial Intelligence / Machine Learning (Amazon Sagemaker, Azure ML Studio)
• Streaming Data Ingestion and Analytics (Amazon Kinesis, Apache Kafka)
• Visual Analytics (Tableau, PowerBI)
• Modern Data Workflows (Apache Airflow, dbt, Dagster)
• Innovations in data platform development and delivery.
• Design and deliver innovative solutions on:
• Amazon Web Services
• Microsoft Azure
• Google Cloud Platform
• Using core cloud data warehouse tools
• Distributed processing engines
• Event streaming platforms, and other modern data technologies.
• Data Engineering consisting of streaming / real-time data solutions, modern data platforms anddata systems within products (i.e., database systems, graph databases, key-value stores,document databases and transactional systems)
• Data Visualization
• Machine Learning and Artificial Intelligence