Data Engineer

A US-based company developing efficient solutions intended to serve and empower seniors and individuals living with disabilities is looking for a Data Engineer. The selected candidate will be documenting the existing data flows and executing a plan to rebuild them. The purpose-driven, venture-funded technology company promotes family and community participation while enabling smarter living environments and healthier lives. The company has managed to raise $30mn+ in funding so far. The engineer will collaborate efficiently with the product management, operations, and other engineers to build high-value solutions.

Job Responsibilities:

• Recreate data connectors, ETL jobs, and dashboards currently in use
• Develop databases and data pipeline/ETL using modern technologies and tools
• Assist the team in developing operationally efficient analytic solutions
• Define standards and methodologies for the data warehousing environment
• Develop easy to scale data pipelines using the latest tools and technologies like AWS, Snowflake, Spark, Kafka to induct data from various systems
• Transform requirements into scalable technical solutions capable of meeting data warehousing design standards
• Build data pipelines and ETL applications that support business operations in advertising, content, and finance/accounting
• Collaborate to decipher data migration issues and improve system performance
• Collaborate efficiently with product management, technical program management, operations, and other engineers

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 3+ years of relevant experience as a data engineer
• Thorough knowledge of building scalable data systems and data-driven products while working with cross-functional teams
• Expertise in utilizing Python, SQL, Apache Airflow, Snowflake, DBT, and Amazon Quicksight
• Must be able to build data pipelines and ETL applications with large data sets
• Ability to build REST APIs for back-end services
• Must possess knowledge of implementing, testing, debugging, and deploying data pipelines using tools like Perfect, Airflow, Glue, Kafka, Serverless (Lambda, Kinesis, SQS, SNS), Fivetran, or Stitch Data/Singer
• Professional experience of working with Cloud data warehousing technologies such as Redshift, BigQuery, Spark, Snowflake, Presto, Athena, and S3
• Experience with SQL DB administration (PostgreSQL, MS SQL, etc.)
• Understanding of complex, distributed, microservice web architectures
• Experience with Python back-end, ETL to move from one database to another
• Solid understanding of analytics needs and proactive-ness to build generic solutions to improve the efficiency