Warner Bros. Discovery - Staff Data Engineer - ETL/Azure Databricks (8-14 yrs)

Roles & Responsibilities :

What You Will Do :

- Design and develop the data platform to efficiently and cost effectively address various data needs across the business.

- Build software across our entire cutting-edge data platform, including event driven and batch data processing, storage, and serving through various data integration techniques such as APIs, Lambda, File Feeds etc.

- Develop and maintain data integrations including direct digital marketing, social channels, etc.

- Ingest, process massive campaign datasets to analyze the campaign performance.

- Change how we think, act, and utilize our data by performing exploratory and quantitative analytics, data mining, and discovery.

- Think of new ways to help make our data platform more scalable, resilient, and reliable and then work across our team to put your ideas into action.

- Help us stay ahead of the curve by working closely with data architects, stream processing specialists, API developers, our DevOps team, and analysts to design systems.

- Work closely with data analysts and business stake holders to make data easily accessible and understandable to them.

- Ensure data quality by implementing re-usable data quality frameworks.

- Work closely with various other data engineering teams to roll out new capabilities.

- Develop and enforce data engineering, security, data quality standards through automation.

- Participate in supporting platform 24X7.

- Be passionate about growing a team - hire and mentor engineers and analysts.

What You Will Need :

- Bachelor's degree in computer science or similar discipline.

- 8+ years of experience in software engineering

- 8+ years of experience in data engineering.

- Go above and beyond attitude.

- Ability to work in fast paced, high pressure, agile environment.

- Ability and willingness to learn any new technologies and apply them at work to stay ahead of the curve.

- Expertise in at least few programming languages - Java, Scala, Python or similar.

- Expertise in building and managing large volume data processing (both streaming and batch) platform is a must.

- Expertise in OLAP databases such as Snowflake or Redshift.

- Expertise in SQL, Spark SQL, Hive etc.

- Expertise in stream processing systems such as Kafka, Kinesis, Pulsar or Similar

- Expertise in building micro services and managing containerized deployments, preferably using Kubernetes.

- Expertise in distributed data processing frameworks such as Apache Spark, Flink or Similar.

- No-SQL (Apache Cassandra, DynamoDB or similar) is a huge plus.

- Experience in operationalizing and scaling machine models is a huge plus.

- Experience with variety of data Tools & frameworks (example: Apache Airflow, Druid) will be a huge plus.

- Experience with Analytics Tools such as Looker, and Tableau is preferred.

- Cloud (AWS) experience is preferred.

- Ability to learn and teach new languages and frameworks.

- Excellent data analytical skills

- Direct to consumer digital business experience preferred.

- Strong interpersonal, communication and presentation skill.