Senior Data Engineer

CodeRoad

. Design and implement modern semantic models, including facts, dimensions, and metric stores using tools like dbt .

Posted 11/1/2026full-timeRemoteSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing semantic models and building resilient ELT/ETL pipelines while ensuring data governance and compliance with PII protection. Proficient in SQL and experienced in collaborating with cross-functional teams to support AI workflows.

Highest-signal resume keywords

Data Engineering ExperienceSQL ProficiencyKimball Dimensional ModelingELT/ETL Pipeline DevelopmentDatabase Security Implementation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

SQLDbtKimball Dimensional ModelingELTETLDatabase TuningData GovernanceRBACRLSDynamic Data Masking

Soft Skills

Proactive Problem-SolvingCollaborative Execution

Tools & Technologies

Azure SQLPostgreSQLAirflowPrefectDagsterPgvectorPineconeQdrantKafkaKinesis

Industry Keywords

Data FoundationsRAG ApplicationsAgentic AIData FreshnessData Redundancy

Tech Stack

Tools & technologies

AirflowAzureCloudETLKafkaPostgresSQLTerraform

About the role

Key responsibilities & impact

Design and implement modern semantic models, including facts, dimensions, and metric stores using tools like dbt
Abstract complex operational databases for AI querying and analytical consumption
Build curated, high-performance analytical views and production ELT/ETL pipelines
Streamline data retrieval, improve freshness, and eliminate redundancy across environments
Tune complex database queries, indexing, and schema definitions using systematic query log analysis
Implement granular data governance, including RBAC, RLS, dynamic data masking, and anonymization for PII protection
Collaborate with cross-functional AI engineering teams on RAG and Agentic AI workflows
Define pipeline monitoring, continuous data quality checks, and automated alerting
Maintain reliability across all analytical layers

Requirements

What you’ll need

4+ years of dedicated data engineering experience
Production-grade command of SQL, including Azure SQL, PostgreSQL, or modern Cloud Data Warehouses
Solid expertise in Kimball dimensional modeling
Experience building resilient ELT/ETL pipelines
Experience structuring semantic/metrics layers using dbt
Proven experience implementing strict database security policies, fine-grained RBAC/RLS, and dynamic data masking for PII compliance
Practical experience tuning queries for low-latency workloads
Experience supporting data foundations for RAG applications and Agentic AI frameworks
Strong technical autonomy and proactive problem-solving mindset
Collaborative approach to driving execution within nearshore agile teams
Advanced/Fluent English proficiency, written and spoken, required
Nice to have: Airflow, Prefect, Dagster, pgvector, Pinecone, Qdrant, Kafka, Kinesis, Terraform

Benefits

Comp & perks

USA Contractor / 100% Remote
Competitive Pay (USD)
Holidays Off & Paid Time Off
Health insurance assistance program
Opportunity to work with high-growth US-based companies and cutting-edge tech stacks
Agentic AI tools and training
Coursera Enterprise
Studio practice labs
High-touch onboarding
Transparent leadership communication
Community recognition
Psychological safety
Continuous multi-project pipeline
Direct engagement with U.S. client teams and roadmaps