Data Engineer

Industry: Software
Company size: 11-50

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Job description

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

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