Interested in building state-of-the-art ETL infrastructure for processing event data from the largest enterprise search deployment on the planet ( 1B search queries/week against 1 trillion records updated at a rate of 34B/day, and growing fast ), and making this data available and accessible to the entire search team in a timely manner to support data-driven decision-making?
Then Search Relevance is your destination! They are looking for an experienced Data Engineer to help build, scale, and maintain these critical systems.
Responsibilities
- Contributing at a senior level to the search data lake & data warehouse design and data preparation by implementing a solid, robust, extensible design that supports key business flows
- Build and implement models in a production environment for a high-impact salesforce product
- Create and maintain overall optimal data pipeline architecture
- Assemble large, complex data sets that meet functional / non-functional business requirements
- Manage data migrations/conversions and own troubleshooting data processing issues
- Create the pipeline for optimal extraction, transformation, and loading (ETL) of data from a wide variety of data sources
- Build machine learning functions to help with data automation and data preparation
- Work closely with their analytics engineers and data warehouse engineers to build analytics tools and dashboards that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics
- Provide operational excellence through root cause analysis and continuous improvement for Big Data technologies and processes
- Create data tools for analytics and data scientist team members that will assist them in building and optimizing their product into an innovative industry leader
- Work with data and analytics experts to strive for greater functionality in their data systems
- Discover more innovative machine learning solutions that can drive business values
Required Skills And Experience
- BS, MS, or Ph.D. in Computer Science or related technical discipline
- 5+ years of relevant work experience
- A passion for building big data platforms
- Proficient coding skills and strong algorithm & data structure foundation
- Knowledge of the tools: Hadoop, Spark, Presto, Hive, or Airflow
- Experience with workflow scheduling systems (Azkaban, Oozie, Airflow, etc.)
- Experience working with one or more file formats (Parquet, AVRO, ORC)
- Experience in getting data through API with one of the following: Python, Java, Scala, etc
- Strong problem-solving skills with a can-do attitude
- Ability to practice software engineering best practices with git and version control systems
- Solid communication skills and the ability to explain complex data pipelines to both technical and non-technical audiences
- Experience with Scrum or other agile development methodologies, with attention to code quality with the mission of delivering secure code
- Experience in successfully mentoring junior SDEs
Not Required, But Bonus If You Have
- Knowledge of NoSQL stores
- Machine learning experience- either in an academic or professional setting
- Kubernetes or docker knowledge
- Experience with Sagemaker, Google Datalab, or Databricks
Accommodations
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