Data Engineer creating leading cloud platform with big data technologies at SS&C. Building models, managing data migrations, and implementing ETL processes for analytics and automation.
Responsibilities
Join a team that creates a leading cloud platform with the latest big data, cloud-native and machine learning technologies
Build and implement models in a production environment for a revenue-driving product
Create and maintain overall optimal data infrastructure
Assemble large, complex data sets that meet functional / non-functional business requirements
Manage data migrations/conversions and troubleshoot data processing issues
Create the pipeline for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources
Build machine learning functions to help with data automation and data preparation
Work closely with our product team and data warehouse engineers to build analytics tools and dashboards that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
Work with other data experts to strive for greater functionality in our data systems
Discover more innovative machine-learning solutions that can drive business values.
Requirements
Bachelor’s Degree in Computer Science, Information Systems or other STEM field
5+ years of experience in data engineering or a related field required
Proficient coding skills and strong algorithm & data structure basis
Knowledge of one or multiple of the tools: Hadoop, Spark, Presto, Hive, Kafka, or Airflow
Skills in transforming data, developing data structures, building a metadata store, and setting up data pipelines or data workflows
Experience in getting data through API with Python or other programming languages such as JavaScript, Java, C#, Scala, etc
Strong problem-solving skills with a can-do attitude
Great software engineering best practices with git and version control systems
Solid communication skills to explain complex data pipelines to both technical and non-technical people
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