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Job Location: remote
- Architecting, building, and maintaining modern, scalable data architectures in the cloud preferably AWS.
- Clean, transform, and analyze vast amounts of raw data from various systems using Spark to provide ready-to-use data to our feature developers and business analysts.
- Involves both ad-hoc requests as well as data pipelines that are embedded in our production environment.
- Design develop frameworks for increasing the overall efficiency of bringing data into the data lake, processing and delivery of data; Encode best practices into reusable tools that can be shared across the team.
- Automate the deployment of changes to production to improve data reliability quality
- Work closely with upstream and downstream stakeholders to collect business requirements and develop data models to satisfy those requirements.
- Design and deliver event-driven solutions using a streaming platform such as Kafka.
- Mentor data engineers and other stakeholders on the best practices of managing a large-scale production data platform and developing a data-driven operations culture within the data engineering team.
- Oversee the migration of data from legacy systems to new solutions.
- Experience with Machine Learning or other leading-edge technologies.
- Exposure to at least two to three domains (such as Sales Marketing, Supply Chain, Finance, Data Science, Analytics).
- ETL Pipeline experience Hadoop Ecosystem, Kafka, Spark
- Workflow management oozie, Airflow
- 5+ years of hands-on experience building large-scale data systems.
- 5+ years of experience with architectural patterns, building APIs, microservices, event streams, and high throughput systems.
- 5+ years of using AWS ecosystem tools preferred, including Redshift, S3, EMR, Lambda, Athena, Kinesis, ECS, Glue, and/or another cloud provider s equivalent stack.
- 5+ years of experience building ETL pipelines and working with Cloud Data Warehouses (such as Redshift, Snowflake, Azure SQL Data Warehouse, Big Query).
- Experience operating very large data warehouses or data lakes.
- Experience designing and implementing data models for enterprise data warehouses.
- Demonstrated Kafka, streaming experience
- 5+ years of experience with ETL tools (Matillion, Informatica, DataStage, Talend)
- Experience working with orchestration tools (Airflow, Luigi, Apache Nifi, Step Functions, etc.)