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Scale Marketing

Data Engineer

Scale Marketing
Chicago, IL Full time Posted 12d ago
Analytics Big Data Bigdata Business Intelligence Data Data Analytics Data Architecture Data Engineer Data Integration Data Pipeline Data Pipelines Data Platform Data Processing Database Databases ETL Hadoop Hbase Hive Nosql Databases Spark SQL Streaming Data
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Job Description

Scale Marketing is hiring a Data Engineer to expand and optimize its data pipeline architecture, data flow, and extraction/transform/load processes. This role is built for collaboration across teams, with a focus on redesigning the company’s data architecture to support next-generation products and data initiatives. The position is onsite in Chicago, IL.

What you’ll work on

  • Create and maintain optimal data pipeline architecture and ensure reliable delivery across systems.
  • Assemble large, complex data sets that align with functional and non-functional business requirements.
  • Identify and implement internal process improvements, including automation of manual work, optimization of data delivery, and infrastructure redesign for scalability.
  • Build infrastructure for data extraction, transformation, and loading from a wide variety of sources using SQL and big data technologies.
  • Develop analytics tools that turn pipeline data into actionable insights for customer acquisition, operational efficiency, and other key performance metrics.
  • Partner with stakeholders across Partner, Client, and Data teams to resolve data-related technical issues and support their data infrastructure needs.
  • Help keep data separated and secure across national boundaries through multiple data centers.
  • Create data tools for analytics and data science teams to support building and optimizing product capabilities.
  • Collaborate with data and analytics experts to improve functionality across the data systems.

What you bring

  • 5+ years of experience in a Data Engineer role.
  • Advanced SQL skills, including experience with query authoring and working familiarity with multiple relational databases.
  • Experience building and optimizing big data pipelines, architectures, and data sets.
  • Ability to perform root cause analysis on internal and external data and processes to answer business questions and identify improvement opportunities.
  • Strong analytic skills with unstructured datasets.
  • Experience building processes for data transformation, data structures, metadata, dependency, and workload management.
  • A track record of extracting value from large disconnected datasets.
  • Working knowledge of message queuing, stream processing, and highly scalable big data data stores.
  • Project management and organizational skills.
  • Experience supporting cross-functional teams in a dynamic environment.
  • Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.

Relevant tools and platforms

  • Big data tooling such as Apache Hadoop, Apache Hive, Apache Spark, Apache Pig, etc.
  • Experience with at least three relational SQL and/or NoSQL databases, such as MongoDB, HBase, Oracle, SQL Server, Cassandra, Neo4j, Redis, and/or Riak.
  • Experience with data pipeline and workflow management tools such as Apache Kafka and/or Apache Spark, Azure DevOps, AWS Data Pipeline.
  • Experience with at least one cloud service: AWS or Microsoft Azure.
  • Experience with at least one stream-processing system: AWS Kinesis, Azure Stream Analytics, Apache Flink, etc.
  • Experience with at least three of: Python, Java, Scala, C++, Linux/Unix, etc.

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