Data Engineer for ML & Analytics in Marketing Platform

Data Engineer (5.0 yr.)

Upper-Intermediate English

Senior

Are you a talented developer looking for a remote job that lets you show your skills and get decent compensation? Join Upstaff.com, a platform that connects you with hand-picked startups and scale-ups in the US and Europe.

Summary

Data Engineer is wanted to join the team building data backbone for a performance marketing platform. You’ll design and operate data streaming pipelines, tracking, and feature store foundations that power both analytics and production ML with real traffic and real budgets

Required Skills

Kafka 5.0 yr.

Snowflake 5.0 yr.

Python 5.0 yr.

Data Analytics 4.0 yr.

Nice to Have

Apache Spark Flink Google BigQuery AWS Redshift Docker CI/CD Google Cloud Platforms Software Engineering Machine Learning

ID: 400-113-906

Last Updated: 2025-11-27

What’s the project about?

A pay-per-lead ML-driven platform needs strong data foundations: fast tracking, reliable ingestion, feature freshness, consistent schemas, and robust quality checks. You’ll architect and maintain the infrastructure that makes ML and analytics possible, trustworthy, and optimized.

Requirements are:

Proven experience building real-time, low-latency data services
Strong background with modern data stack (e.g., Kafka/Kinesis, Spark/Flink/Beam, Snowfl ake/BigQuery/Redshift)
Ability to design schemas, ingestion fl ows, and data quality frameworks
Experience collaborating with ML teams on feature availability and consistency

What will you do?

Build and maintain real-time data pipelines for performance-based marketing platform
Design event schemas, ingestion flows, and data quality guardrails
Help establish an internal feature layer (online/offline consistency)
Support ML teams with fast, reliable data signals
Operate high-throughput systems in production environments

Technical skills required:

Solid Python coding
Real-time data systems: Kafka/Kinesis, Spark/Flink/Beam
SQL and data modeling
Experience building distributed, high-load systems
Data quality, data validation
DevOps skills: Docker, monitoring

Nice to have:

Experience supporting ML systems (feature serving, online/offline consistency)
Production experience with model inference pipelines
Strong DevOps experience (Docker, Kubernetes, CI/CD)
Experience with cloud-native architectures (AWS/GCP)
Experience implementing data observability / lineage frameworks

Not your tech stack?

Join the Upstaff community and we are looking for the best project for you. Be ready for the next steps:

Create your profile on our website (import from LinkedIn)
20-30-minute screening call
Technical interview
Feedback
Project Selection (we are looking for the best project for you).

We work with developers from 50+ countries in different regions: Europe, LATAM, the U.S. (W-9 form owners), Canada, Asia (Philippines, Indonesia), Oceania (Australia, New Zealand, Papua New Guinea), and the the UK.

We don’t have a legal and ethical basis to accept applicants from the following countries: Russia, Belarus, Iran, North Korea
We do not provide visa assistance, and our cooperation model does not include the benefits typically offered with direct hire.