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