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