Data Engineer

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.)