Data Engineer - Media Data Engineering

Bloomberg Media empowers global business leaders with breaking news, expert opinion, and proprietary data distributed on every platform, across every time zone, reaching over 80 million unique visitors a month through its digital properties. Our products require scalable and performant data services to deliver the best content and experiences to our users.

Media Data Engineering is responsible for maintaining a variety of data sets in our Data Lake. We own a data pipeline comprising dozens of ETL jobs that ingests and aggregates these data sets in our Data Lake. The entire platform is running on a multi cloud environment built using a mix of open-source and public cloud technologies. This data empowers our Data Science and Analytics teams to improve our customers' experiences through machine learning, A/B testing, and data-driven decision making. Finally, we support product managers, marketers, and analysts with data reporting tools and integration of the data sets from our Data Lake with customer data platform (CDP).

As a member of the team, you will work with a wide range of stakeholders such as Product, Editorial, Ad Operations, Marketing, and other engineering teams. You will maintain, expand, and innovate our ETL infrastructure by leveraging open source and cloud technologies. You’ll also work closely with analysts and data scientists to provide the data and tooling they need to generate insights that will improve the experience of Bloomberg Media customers. With the help of Google Cloud technologies like BigQuery and Dataproc you'll empower them with the compute platform they need to train machine learning models and generate predictions.
You’ll have opportunities to grow your network by playing a central role in empowering other teams with a large collection of data sets that lie in a critical path for management and finance reporting for the Bloomberg Media business.

• Develop and maintain data pipelines flowing terabytes of new data every day.
• Innovate and improve the platform by applying the best practices in the Data Engineering field, in particular focusing on improving data quality, data observability and data discovery as we look to scale up our platform both in terms of size and complexity.
• Develop the domain knowledge and strategic thinking necessary to identify opportunities to grow the impact of our team through ideation, project proposals, and technical discussions.
• Build a network with stakeholders and leverage it to maximize you and your team’s impact.

• Experience developing data extraction, transformation, and load (ETL) pipelines.
• Experience with workflow management technologies such as Airflow, Luigi, NiFi, Oozie.
• Experience with cloud technologies such as AWS, GCP, Azure.
• Experience working on complex data systems from design to delivery.
• Experience with SQL.
• Experience with NoSQL technologies like Elasticsearch, Solr, Cassandra, HBase, etc..
• BA, BS, MS, PhD in Computer Science, Engineering or related technology field.

• Experience with big data systems such as BigQuery, Redshift.
• Experience with Apache Hadoop and Spark running big data processing jobs.
• Experience supporting data scientist workflows.
• Experience integrating with 3rd party APIs.
• Experience managing compute instances, databases, etc. to drive data wrangling and delivery.

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email amer_recruit@bloomberg.net.