Principal Data Architect, Data Science

Egen

. Design and build data ingestion pipelines for feature engineering and machine learning .

Posted 10/15/2026full-timeRemote • United StatesLead💰 $180,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building data ingestion pipelines, utilizing SQL and Python for feature engineering and machine learning. Proficient in deploying solutions on Google Cloud and ensuring data accuracy and reliability while collaborating with cross-functional teams.

Highest-signal resume keywords

Expert-Level SQLExpert-Level PythonData Ingestion Pipeline DesignMachine Learning Model OptimizationGoogle Cloud Platform Deployment

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ScienceFeature EngineeringPredictive ModelingClusteringText AnalyticsPCAAutomated TestingCI/CDETLData Visualization

Soft Skills

CommunicationCollaboration

Tools & Technologies

Apache SparkDockerSalesforceNoSQL Databases

Industry Keywords

Healthcare DataExploratory Data AnalysisData ProcessingStructured DataUnstructured Data

Tech Stack

Tools & technologies

ApacheCloudDockerETLGoogle Cloud PlatformNoSQLPythonSparkSQL

About the role

Key responsibilities & impact

Design and build data ingestion pipelines for feature engineering and machine learning
Create predictive features using healthcare data, statistics, and data science
Perform feature extraction and selection using clustering, text analytics, and PCA
Conduct exploratory data analysis to identify patterns, trends, and relationships
Experiment with statistical and machine learning methods to build, tune, and optimize predictive models
Ship production code following engineering best practices
Document work and communicate approaches, insights, and solutions to technical and non-technical audiences
Build and maintain pipelines and processes supporting enterprise data science products
Ensure data and outputs remain accurate and reliable
Partner with stakeholders, data scientists, data engineers, and product managers to deliver data products
Work with Google Cloud and Salesforce platforms to help clients drive action and impact through data and insights

Requirements

What you’ll need

6+ years working across data science and machine learning (for the Lead level)
Expert-level SQL and Python
Hands-on work with structured and unstructured data, such as tables, text, images, and video
Experience with relational (SQL) and non-relational (NoSQL) databases
Familiarity with ETL and data processing tools like Apache Spark
Experience using tools to visualize data and monitor its health
Comfort with automated testing and CI/CD
Experience with Docker
Experience deploying to GCP or another cloud platform
All roles are subject to standard hiring verification practices, which may include background checks and employment verification

Benefits

Comp & perks

Comprehensive Health Insurance
Paid Leave (Vacation/PTO)
Paid Holidays
Sick Leave
Parental Leave
Bereavement Leave
401 (k) Employer Match
Employee Referral Bonuses
Background checks, employment verification, and other standard hiring verification practices
Equal opportunity, inclusion, diversity, and equity commitment
Reasonable accommodations during all aspects of the selection process