Data Engineer

• Work on designing databases and data pipelines/ETL using the latest technologies and tools
• Assist the development team to build operationally efficient analytic solutions
• Define standards and methodologies for the Data Warehousing environment
• Design and develop scalable data pipelines utilizing modern tools and technologies like AWS, Snowflake, Spark, and Kafka to induct data from various systems
• Translate complicated business requirements to scalable technical solutions to meet data warehousing design requirements
• Build easy to scale data pipelines and ETL apps to support business operations in areas like advertising, content, and finance/accounting
• Assist with deciphering data migration issues and improving system performance
• Work closely alongside product management, technical program management, operations, and other engineers

Job Requirements:

• Bachelor s/Master s degree or Ph.D. in Engineering, Computer Science (or equivalent experience)
• At least 3+ years of relevant experience as a Data Engineer
• At least 2 years of experience working with Python
• Should possess a deep understanding of Django with the ability to build APIs
• Thorough knowledge of building scalable data systems and data-driven products working while working with cross-functional teams
• Must be able to build data pipelines and ETL applications with large data sets
• Must have a thorough knowledge of developing REST APIs for back-end services
• Familiarity of implementing, testing, debugging, and deploying data pipelines using tools like Prefect, Airflow, Glue, Kafka, Serverless (Lambda, Kinesis, SQS, SNS), Fivetran, or Stitch Data/Singer
• Familiarity with Cloud data warehousing technologies like Redshift, BigQuery, Spark, Snowflake, Presto, Athena, and S3
• Understanding of SQL DB administration (PostgreSQL, MS SQL, etc.)
• Nice to have some DevOps experience
• Knowledge complex, distributed, and microservice web architectures are preferable
• Deep understanding of analytics needs and proactive-ness to build generic solutions for improving efficiency