Senior Data Engineer

Industry: Healthtech
Company size: 251-10K
Not disclosed

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Job description

A leading all-in-one technology platform that is powering the cannabis industry with advanced solutions is looking for a Senior Data Engineer. The selected candidate will be tasked with defining the next generation of data warehouse and data lake architecture, its roles, and access management. The company is dedicated to providing customers with the best cannabis products from leading brands. The company has managed to raise more than $600 mn during their Series D round of funding. This will be an exciting opportunity for the developer to build unique, innovative products. 


Job Responsibilities:

  • Build, maintain, and operate scalable, performant, and containerized infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using AWS services
  • Ingest data from a range of external data sources to Snowflake & S3
  • Design, create and own strong, scalable data processing and data integration pipelines using Python, dbt, Kafka, Fivetran, Airflow/Dagster, Spark, REST API endpoints, and Microservices
  • Make data frameworks that aid with data quality, integrity, integration, and self-service
  • Assist the Analytics Engineering team in ensuring the data warehouse's performance and dependability
  • Identify data requirements for business and product teams, as well as metrics and analytical requirements
  • Orchestrate complex data flow patterns across many different tools
  • Assemble and implement a pattern language across the data stack to ensure accurate event taxonomy and tables
  • Implement data compliance policies and tooling with the help of the Data Governance team
  • Assist in the development and administration of the Snowflake Data Warehouse and other data tools

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 5+ years of hands-on experience designing, creating, and sustaining scalable data pipelines 
  • Familiarity with Python, API calls, and scripting languages
  • Demonstrated experience writing clean, efficient, and well-documented Python code 
  • Willingness to become effective in other languages as needed
  • Competency in composing complex, highly-optimized SQL queries across extensive data sets
  • Experience with cloud technologies AWS Infrastructure and services or Google Cloud Services
  • Experience with IaC technologies like Terraform
  • Experience with Snowflake (BigQuery, Redshift), PostgreSQL
  • Experience with event streaming technologies like Kafka
  • Track record of experience working with containers and container orchestration tools like Docker and Kubernetes
  • Experience with transforming, developing data structures, metadata, dependency, and data workflows to support the Analytics, Data Science, and ML functions
  • Skilled at project management and capable of working autonomously
  • Familiarity with Fivetran, dbt, Airflow/Dagster, Datadog, Jupyter Notebook, JavaScript, R, Looker/Tableau, Databricks, Dremio, Datafold, and modern data stack is nice to have
  • Nice to have some experience with Microservice architecture

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