Data Engineer: Cloud Data Platforms & AI Analytics

Slalom; Atlanta (GA); On-site; USD 100,000 - 115,000; Full time

Benefits offered by this job

Meaningful time off and paid holidays

Parental leave

401(k) with match

Subsidized health, dental, & vision

Job summary

Slalom in Atlanta is seeking a Data Engineer to join our Data Architecture & Engineering team. You will design and implement data platform components across AWS, Microsoft Azure, and Google Cloud, shaping modern data platforms for leading organizations.

You will collaborate in cross-functional teams, translate complex requirements into tasks, and ensure high-quality, timely delivery while advancing streaming, warehousing, and AI-enabled data initiatives.

Qualifications

• 4+ years of hands-on data engineering in production environments.
• Experience with modern data technologies and cloud platforms.
• Proficiency in Python and Java.

Responsibilities

• Designing and implementing components of clients’ data platform solutions, typically under the direction of a Solution Architect.
• Translating complex requirements into actionable development tasks.
• Ensuring timely, high-quality delivery of development items for yourself and the data engineers you support.
• Building solutions using cloud data warehouses, distributed processing engines, event streaming platforms, and more.
• Working across data engineering disciplines, including streaming, modern data platforms, data architecture, and AI-accelerated data engineering.

Skills

Data engineering

Cloud platforms

Python

Java

Tools

Amazon Redshift

Snowflake

BigQuery

Azure Synapse Analytics

Amazon EMR

Apache Spark

Presto

Databricks

Amazon Kinesis

Apache Kafka

Job description

Slalom in Atlanta is seeking a Data Engineer to join our Data Architecture & Engineering team. You will design and implement data platform components across AWS, Microsoft Azure, and Google Cloud, shaping modern data platforms for leading organizations.

You will collaborate in cross-functional teams, translate complex requirements into tasks, and ensure high-quality, timely delivery while advancing streaming, warehousing, and AI-enabled data initiatives.