Data Engineer (Marketing & Analytics Focus)

Remote (except Russia, Belarus).

The ultimate AI life assistant, mentor, therapist, friend. Whatever you need, really, Replika is there for you. Right now, we’re rebranding with one of the world’s top design agencies, scaling our global team, and pushing human-AI connection further than ever. We’re the humanists in AI. And we’re making sure it’s done right.

What you’ll do

1. Design and maintain robust data pipelines integrations: Google Ads, Firebase, AppsFlyer, and Amplitude
2. Drive analytics infrastructure and tooling to eventually build first class scalable data platform
3. Build and manage orchestration workflows using Airflow
4. Maintain and optimize data warehouses and databases (ClickHouse, Postgres, MongoDB, S3)
5. Ensure clean, well-documented event tracking and accurate data mapping across systems
6. Diagnose data quality issues and propose scalable solutions
7. Build and maintain ETL/ELT processes for marketing events data
8. Support Tableau dashboards, maintain jobs and extraction tasks
9. Collaborate with Growth, Analytics, and Engineering teams to improve marketing attribution and event analytics
10. Identify gaps, data anomalies, and areas for improvements in current infrastructure

Requirements

1. 3+ years in Data Engineering, Analytics Engineering, or similar role
2. Strong experience working with:
3. Amplitude (very important)
4. Airflow for data orchestration + ML Pipelines
5. AppsFlyer events data (or Adjust)
6. Proficient in SQL (Postgres, ClickHouse, Athena), database performance tuning, query optimization
7. Strong knowledge of ETL/ELT pipeline building best practices
8. Working experience with AWS pipelines, S3 buckets (data storage and retrieval)
9. Familiarity with MongoDB
10. Experience troubleshooting and validating event-based tracking and attribution models
11. Understanding of marketing analytics and common metrics (CPI, ROAS, retention, etc.)
12. Experience connecting and troubleshooting data sources for Tableau visualizations (or other BIs)
13. Comfortable diagnosing and documenting data flows and source-of-truth issues

Nice to Have

1. Familiarity with big data processing frameworks (e.g., Spark, dbt, etc.)
2. Experience with infrastructure-as-a-code tooling, e.g. Terraform
3. Working with dialogue and text data
4. Knowledge of data governance and privacy standards (GDPR, CCPA)
5. Experience working with real-time data ingestion (streaming pipelines)

What we offer

1. Competitive salary based on your experience and skill set
2. Opportunity to build an AI product that deeply impacts users
3. Expect to work some European hours, as the team is in Europe. Potential visa support is available
4. Global off-site meetings, including gatherings in San Francisco