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Job Overview

We are looking for a Machine Learning Data Engineer who is passionate about all things data. You will be working on enhancing top-flight datasets and innovative data products. Data quality and best practices are at the core of our team ethos as we support a fast-moving, highly cross-functional organization.


  • AWS, GCP, and On-prem Ecosystem
  • Python, Spark, Snowflake, Big Query, Postgres, Hive, HDFS, Parquet
  • Kubernetes, Docker
  • Pytorch, ONNX
  • Airflow



  • Automate manual tasks from data science and create tools for data scientists to simplify future automation
  • Build and enhance current data warehousing architecture to provide insights and analytics to our internal and external clients
  • Develop and release via CI/CD and agile methodologies
  • Automate and maintain infrastructure builds in AWS/On-Prem/GCP to support applications running in Kubernetes (Terraform, Ansible, Chef)
  • Build shared components and/or frameworks that improve engineering productivity across the organization
  • Create and maintain documentation of services, tools, and frameworks
  • Play a key role in building the ETL/ELT stack to cleanse, transform and load data from different sources using multiple technologies
  • Ensure that data is easily discoverable and usable for data scientists and analysts across the company
  • Identify root causes of instability in a large-scale distributed system, across stacks


2+ years experience with:

  • a scripting language like Python, or JavaScript
  • writing SQL statements
  • building and optimizing workflows that cross, columnar stores, row-level stores, and transactional databases. (OLTP databases such as Postgresql, MySQL; OLAP databases such as Snowflake, BigQuery, Redshift; and NoSQL databases such as DynamoDB, MongoDB, Couchbase)
  • developing data pipelines for at least terabyte volumes of data
  • modeling, measuring, and analyzing complex data
  • server-side concepts such as microservices, databases, caching, monitoring, and scalability
  • schema design and dimensional data modeling
  • distributed data technologies for building efficient & large-scale data pipelines like Hadoop, MapReduce, Spark, Flink, Kafka

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VideoAmp Overview

The VideoAmp Platform enables advertisers to optimize their entire portfolio of linear TV, OTT and digital video to business outcomes, measuring how their ads performed against metrics that matter. Powered by the largest, highest quality commingled TV datasets and data science methodologies built from the ground up, we have created a privacy-compliant suite of solutions for advertisers, agencies and publishers to discover, amplify and analyze the entire path to conversion.

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