Senior Data Engineer

Quick Facts

• Role: Senior Data Engineer

• Work style: Fully remote

• Focus: Large-scale social and web data engineering, metrics, data quality, and rapid prototyping

Description

The Senior Data Engineer will take technical ownership of data solutions for extracting, transforming, and scoring signals from large social and web datasets. The role combines engineering, data discovery, metric development, data quality, and rapid prototyping, with full responsibility for correctness and quality. You will translate ambiguous product and business needs into clear technical solutions.

Responsibilities

• Own the technical approach for extracting, transforming, and scoring signals from large social and web datasets

• Design and develop reliable data transformations and pipelines

• Evaluate and incorporate new data sources into existing workflows

• Define and validate metrics used to identify meaningful trends and signals

• Own complex technical implementation across the workstream

• Translate ambiguous business/product requirements into technical solutions

• Clean and prepare large datasets while ensuring data quality and consistency

• Build automated testing into data transformations and pipelines

• Develop rapid prototypes to validate technical approaches before full implementation

• Deliver clean, reusable code, pipelines, and datasets

• Support technical decisions and help shape the approach to new data challenges

• Use AI-assisted development tools while maintaining full ownership of engineering quality and correctness

Requirements

• 5+ years of commercial experience in data engineering, analytics engineering, or another strongly technical data role

• Strong hands-on experience with Python and SQL

• Strong practical experience with dbt

• Experience working with Snowflake

• Experience building or developing reliable data pipelines and transformations

• Strong understanding of data quality and automated testing

• Ability to independently own complex technical problems from definition through implementation

• Experience translating business or product requirements into technical solutions

• High level of autonomy, technical judgement, and ownership

Benefits

• Fully remote work

• High level of technical ownership and autonomy

• Real influence on how new data sources, metrics, and technical approaches are developed

• Hands-on work with Python, SQL, dbt, and Snowflake

• Opportunity to solve technically complex problems using large and diverse datasets

• Opportunity to combine engineering with experimentation, data discovery, and rapid prototyping

• Close collaboration with senior data leadership

• Opportunity to shape engineering and data quality practices within the workstream

• Access to modern AI-assisted development tools

• Multisport card

• Private healthcare