Please mention DailyRemote when applying
AI Summary
Own the end-to-end data platform including ingestion pipelines, transformation layers, and semantic modeling. Build the data foundation to enable AI services by unifying fragmented research data sources.
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
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
Automatically Apply to the Best Remote Jobs
Stop the endless job search. Our AI finds and applies to the best jobs for you.
