Senior Data Engineer

2 days ago

Seattle, Washington, United States CyberTec Full time
Job Description

CyberTec is seeking a highly skilled Senior Data Engineer to join our Ads & Data Platforms team. As a key member of our Content Engineering team, you will be responsible for designing and developing scalable data warehousing solutions, building ETL pipelines in Big Data environments, and collaborating with Data Product Managers, Data Architects, and Data Engineers to deliver successful data solutions.

Responsibilities:

  • Contribute to the design and growth of our Data Products and Data Warehouses around Content Performance and Content Engagement data.
  • Design and develop scalable data warehousing solutions, building ETL pipelines in Big Data environments (cloud, on-prem, hybrid).
  • Help architect data solutions/frameworks and define data models for the underlying data warehouse and data marts.
  • Collaborate with Data Product Managers, Data Architects, and Data Engineers to design, implement, and deliver successful data solutions.
  • Maintain detailed documentation of your work and changes to support data quality and data governance.
  • Ensure high operational efficiency and quality of your solutions to meet SLAs and support commitment to our customers (Data Science, Data Analytics teams).
  • Be an active participant and advocate of agile/scrum practice to ensure health and process improvements for your team.

Qualifications:

  • 7+ years of data engineering experience developing large data pipelines.
  • Strong SQL skills and ability to create queries to extract data and build performant datasets.
  • Hands-on experience with distributed systems such as Spark, Hadoop (HDFS, Hive, Presto, PySpark) to query and process data at large scale.
  • Experience with at least one major MPP or cloud database technology (Snowflake, Redshift, Big Query).

Preferred Qualifications:

  • Nice to have experience with Cloud technologies like AWS (S3, EMR, EC2).
  • Solid experience with data integration toolsets (i.e Airflow) and writing and maintaining Data Pipelines.
  • Familiarity with Data Modeling techniques and Data Warehousing standard methodologies and practices.
  • Good Scripting skills, including Bash scripting and Python.
  • Familiar with Scrum and Agile methodologies.

Education:

  • Bachelor's degree in computer science, Information Systems or related field.

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