About Bigabid
Bigabid focuses on solving the key challenge of growth for mobile apps by building Machine
Learning and Big Data-driven technology that can both accurately predict what apps a user will like
and connect them in a compelling way.
Our technology operates at scale well beyond many of the largest Internet companies, processing
over 50 TB of raw data per day. We handle over 4 million requests per second and interact with over
a billion unique users a week.
Our innovative platform is cutting-edge with a strong product-market fit. As a result, we're seeing
remarkable growth and close to zero customer churn. To support our hyper-growth and continue
propelling the growth of some of the biggest names in the mobile industry, we offer a wide range of
opportunities for different skill levels and experiences.
About the position
We are looking for a data centric quality driven analyst focusing on data process observability. The
person is passionate about building high-quality data products and processes as well as supporting
production data processes and ad-hoc data requests.
As a Data OPS at Bigabid, you will be in charge of the quality of service as well as quality of the data
and knowledge platform for all Bigabids data processes. Youll be coordinating with stakeholders
and play a major role in driving the business by promoting the quality and stability of the data
performance and lifecycle and giving the Operational groups immediate abilities to affect the daily
business outcomes.
Responsibilities
Process monitoring - managing and monitoring the daily data processes; troubleshooting
server and process issues, escalating bugs and documenting data issues.
Metadata store ownership - Creating and maintaining the metadata store; Managing the
metadata system which holds meta data of tables, columns, calculations and lineage.
Participating in the design and development of the knowledge base metastore and UX. In
order to be the pivotal point of contact when needing information on tables, columns and how
they are connected. I.e., What is the data source? What is it used for? Why are we
calculating this field in this manner?
Data quality automation - Creating and maintaining data quality tests and validations using
python code and testing frameworks.
Ad-hoc operation configuration changes - Be the extension of the operation side into the data
process; Using SQL to extract specific client relevant data points and calibrate certain
aspects of the process.
Requirements:
Atlassian
Zillow
Encora Inc.
Forbes Advisor
Our Future Health
