Analytics Data Engineer

Industry: Healthtech
Company size: 51-250

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Job description

A leading healthtech company committed to providing physicians and their patients with vast choices in medical aesthetic treatments and procedures is looking for an Analytics Data Engineer. The engineer will join the team with solid data engineering and analytical skills to support the data and analytics initiatives across global business functions. The company is helping to transform the industry by bringing innovation, forward-thinking technology, and disrupting the status quo. This will be a nice opportunity for candidates to showcase their abilities while growing their careers.


Job Responsibilities:

  • Join the team and support analytics and data initiatives across the company’s worldwide business functions
  • Integrate data from various external and internal sources into a universal data warehouse model
  • Build and maintain ELT data pipelines, suggest and implement the correct data models, and work comfortably in a DataOps environment
  • Effectively communicate with the analytics and business team and help in driving value to the company’s business
  • Work collaboratively with the team members to gather business requirements, lay down successful analytics results, and design data models
  • Design, build, and extend dbt or/and other ELT code to broaden the Enterprise Dimensional Model 
  • Be accountable and responsible for owning delivery outcomes and stakeholder relationships
  • Liaise between analytics professionals, business, and data
  • Contribute to prioritization and planning discussions
  • Conduct continuous exploration of ways to provide new insights and value to ensure relevance and meaningfulness of data 

Job Requirements:

  • Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
  • At least 3+ years of relevant experience as an analytics data engineer 
  • High proficiency in coding in Python and SQL, R or Scala
  • Must be experienced in cloud data warehouses like Databricks, Snowflake, Redshift, Hadoop, Hive, and BigQuery
  • Data transformation/extraction/orchestration tools like dbt, Dataform, Fivetran, Prefect, Airflow, Stitch, Matillion, and Kafka
  • Possess an in-depth understanding of data modeling for visualization, reporting, and data analysis
  • Prior experience in cloud vendors or analytics services such as Glue, Athena, Google Dataproc, Lambdas, etc.
  • Comfortable working with AzureDevOps or Git, CI/CD pipelines, and DataOps
  • Relevant certifications would be highly considered
  • Prolific experience with any one or more of these business subject areas: marketing, finance, healthcare, product, sales, engineering, or customer success 
  • A critical thinking mindset, along with the ability to find gaps and develop plans to address them 
  • Prior experience in machine learning, predictive analytics, and statistics is nice to have 
  • Must be fluent in written and verbal English

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