Data Engineer

Job Description

Data Engineer What you'll be doing: ● [Data Modeling & Design] You will be working with Business, Product and Engineering teams to design, document and implement data tracking and modeling for product features. ● [Data Pipeline & ETLs] You will be responsible for building data pipelines using SQL and/or Python, and creating tables and views for business reporting and analysis needs. You are not only expected to construct datasets that are useful and scalable, but also are expected to make constant changes to existing and new data pipeline jobs to reflect new business requirements and optimize ETL pipeline performance. ● [Ad Hoc Analyses] You will be responsible for providing analytical insights to empower Sales, Marketing, Product and Engineering teams. ● [Data Integrity & Data Bug Investigations] You will be responsible for monitoring, investigating and driving intra-team communications on data issues. ● [A/B Testing Design & Executions] You will be responsible for designing and performing A/B testings to track outcomes of recommendation engine video content suggestions, be able to make sense of the testing data and constantly adjust concurrent tests and strive to optimize the recommendations towards the set KPI We'll be excited if you have: ● Highly proficient in SQL ● Highly experienced in data transformation and modeling tools such as DBT ● Proficient in Python or any other programming language ● Working experience with one of the popular orchestration tools such as Airflow ● 1 to 3+ years professional work experience in data or information technology space ● Attention to detail and bias to action: pursue data quality, troubleshoot data validation, and see issues to resolutions ● Experience partnering with data engineering to develop high data integrity, automated reporting and insightful ad-hoc analyses that illuminate traffic volume, consumer engagement, funnel interaction, conversion rates opportunities within acquisition and product flows ● A proven problem solver who can quickly assess quantitative data sets and distill key insights using analytics and statistical methods ● Familiar with data analytics platforms such as Looker or Tableau ● Experience with big data technologies such as SparkSql, Athena, or Druid would be a big plus ● Outstanding communications skills with both technical and non-technical colleagues. ● BS or MS in a quantitative field (statistics, mathematics, economics, finance, operations research, etc.) Show more Show less