Last Update Last Updated: February, 2026

⛔ This job is currently unavailable

Data Engineer for ML & Analytics in Marketing Platform

Data Engineer (5.0 yr.).

Senior
Upper-Intermediate English

Required Skills

Kafka
Kafka
5.0 yr.
Snowflake
Snowflake
5.0 yr.
Python
Python
5.0 yr.
Data Analytics
4.0 yr.

Nice to Have

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

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

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.

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.
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