Description:

Docker is a remote-first company that simplifies the lives of developers creating world-changing applications.
The company is seeking a Senior Data Engineer to join the Data Engineering team, which is led by the Director of Data Engineering.
The team transforms billions of data points from Docker products and services into actionable insights to influence product strategy and development.
The role involves designing and implementing event ingestion, data models, and ETL processes for mission-critical reporting and analysis while ensuring privacy and compliance.
The Senior Data Engineer will help lay the foundation for ML infrastructure to support data scientists and enhance analytics capabilities.
The data stack includes Snowflake as the central data warehouse, DBT/Airflow for orchestration, and Looker for visualization and reporting.
Data sources include Segment, Fivetran, S3, Kafka, and various other cloud systems.
Responsibilities include managing ETL jobs, building the Central Data Model, integrating new methodologies, and supporting stakeholders across the company.
The first 30 days will involve onboarding, understanding current data architecture, and identifying quick wins for improvement.
By the end of the first 90 days, the engineer is expected to contribute to data engineering projects and recommend improvements.

Requirements:

A minimum of 4 years of relevant industry experience is required.
Candidates must have experience in data modeling and building scalable data pipelines with complex transformations.
Proficiency with a Data Warehouse platform, preferably Snowflake or BigQuery, is necessary.
Experience in data governance, access, and security controls is required, with a strong preference for Snowflake and dbt experience.
Candidates should have experience creating production-ready ETL scripts and pipelines using Python and SQL, as well as orchestration frameworks like Airflow, Dagster, or Prefect.
Experience in designing and deploying high-performance systems with reliable monitoring and logging practices is essential.
Familiarity with at least one cloud ecosystem (AWS, Azure, or Google Cloud) is required.
Experience with a comprehensive BI and visualization framework, such as Tableau or Looker, is necessary.
Candidates should have experience working in an agile environment on multiple projects and prioritizing work based on organizational needs.
Strong verbal and written English communication skills are required.