Data Engineer
Remote US
Updated on 2/9/2024
Seamless.AI

201-500 employees

Intelligent sales prospecting software
Company Overview
Seamless.AI's mission is to help the world connect to opportunity and positively impact billions. The company helps teams maximize revenue, increase sales and acquire total addressable markets instantly using artificial intelligence.
AI & Machine Learning

Company Stage

Series A

Total Funding

$77.7M

Founded

2018

Headquarters

Worthington, Ohio

Growth & Insights
Headcount

6 month growth

-3%

1 year growth

-4%

2 year growth

24%
Locations
United States
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Redshift
Python
Apache Spark
Java
AWS
Hadoop
CategoriesNew
Data & Analytics
Requirements
  • Minimum of 3 years of experience as a Data Engineer or in a similar role
  • Strong proficiency with Python, AWS, and common frameworks used in data ingestion and transformation
  • Hands-on experience building and optimizing large scale data pipelines, architectures, and data sets
  • Knowledge of data warehousing concepts, including data modeling, data cleaning, and ETL processes
  • Strong understanding of database design and data management principles
  • Experience with AWS cloud services such as EC2, S3, Redshift, DynamoDB, and others
  • Strong problem-solving skills, and the ability to analyze data and design solutions to complex data issues
  • Excellent communication and teamwork skills, and a passion for data
  • Experience with other programming languages (e.g., Java, Scala) is a plus
  • Familiarity with big data tools (e.g., Hadoop, Spark) is a plus
Responsibilities
  • Design, develop and optimize data ingestion pipelines to handle real-time and batch data streams using a variety of sources
  • Utilize extensive knowledge of Python and AWS to engineer solutions for the transformation, consolidation, and storage of large datasets
  • Collaborate with data scientists and other stakeholders to understand data needs and translate them into data systems and pipelines
  • Enhance the data ecosystem by leveraging industry best practices for testing, deployment, and runtime environments
  • Drive continuous improvements to data reliability, efficiency, and quality
  • Document data architectures, procedures, and data flows, maintaining excellent communication with the team and stakeholders
  • Monitor data systems performance, troubleshoot data issues, perform root cause analysis, and ensure the implementation of optimal solutions
  • Participate in data governance and ensure adherence to data security and privacy standards
Desired Qualifications
  • Experience with other programming languages (e.g., Java, Scala)
  • Familiarity with big data tools (e.g., Hadoop, Spark)