Nitka Technologies develops software for customers in the US and Europe and brings together about 300 professionals from Eastern Europe, North and South America. We are looking for a Senior Data Engineer for a long-term project to own the end-to-end data platform: ingestion pipelines, transformation layers, semantic modeling, and data governance. You will build the data foundation that enables AI services to reason over structured and unstructured research data - turning fragmented sources into a unified intelligence layer. Our customer is a US-based company that drives intelligent growth for businesses by combining consumer research with brand marketing, product design, and digital engineering to build profitable customer relationships. We offer 100% remote, full-time work with a flexible schedule with core overlap during US working hours (PST). Responsibilities: -Build and manage data pipelines: ingestion from APIs/files, transformations across layers, schema evolution, and collectors from 10+ external sources; -Design semantic models and hybrid search for AI; own star schema with bridge tables and performance optimization; -Enforce governance: access controls, licensing registry, quality monitoring, and retention for GDPR/CCPA; -Manage cloud infrastructure, monitoring, SLAs, cost optimization, and CI/CD; -Deliver client views, multi-cloud exports, and partner with delivery teams for dashboards and AI tools. Requirements: -5+ years of data engineering experience with production-scale cloud data warehouses; -Strong proficiency in a modern cloud data warehouse (Snowflake, BigQuery, Redshift, or Databricks); -Advanced SQL; -Experience building event-driven pipelines on a major cloud provider (AWS Lambda/Step Functions, GCP Cloud Functions, or Azure Functions); -Experience with dimensional data modeling (star schema, slowly changing dimensions, fact tables) and governed transformation layers; -Familiarity with REST API integration; -Proficiency in Python for pipeline orchestration, data transformation, and cloud SDK usage; -Comfortable with infrastructure-as-code (Terraform, CloudFormation, CDK, or Pulumi). Nice to have: -Understanding of how data is structured and served to AI/ML systems; -Familiarity with dbt or similar transformation frameworks; -Experience with data quality frameworks (Great Expectations, Monte Carlo, or native warehouse quality functions). Working conditions: -Remote work -Full-time (8 hours/day) -Flexible schedule with core overlap during US working hours (PST) -Attractive USD compensation -Paid vacation, holidays