Data Engineer Vital IT Services - 5.0 Allen, TX Job Details Full-time $85,000 - $115,000 a year 9 hours ago Qualifications Performance monitoring Data integrity assurance Data model design Athena Azure SQL Database Commercial use (data warehousing systems) Cloud analytics services Data Integration (Data management) Database compliance measures Cloud security engineering Query plan analysis Data Retention (Data management) Data retrieval time improvement SOC 2 Database security hardening Schema design Security compliance frameworks implementation 3 years Snowflake Programming languages Production systems ETL process automation Data integrity process (data warehousing) Azure Cosmos DB Airflow Finance industry (data warehouse design experience) Azure Data Factory Data access controls implementation Retention policy implementation Cloud compliance Full Job Description Core Focus To design, build, and maintain highly reliable data pipelines, storage systems, and transformational schemas; ensuring that secure, clean, and optimized data flows continuously across all core SaaS products and client reporting systems.

Roles & Responsibilities ETL & Data Pipeline Engineering:

Designing, constructing, and maintaining automated data pipelines (ETL/ELT) to ingest, clean, and transform disparate data sources into organized, high-performance repositories.

Database & Schema Modeling:

Designing logical and physical database schemas across relational (e.g., SQL Server, Azure SQL) and non-relational (e.g., Cosmos DB) platforms to support application scale and fast query execution.

Data Warehousing & Architecture:

Building and optimizing centralized data warehouses or staging environments that aggregate complex transactional insurance data for downstream reporting systems.

Query Performance Tuning & Optimization:

Monitoring, profiling, and tuning database performance - including query execution plan analysis, index optimization, and storage strategy adjustments.

Data Security & Compliance Blueprinting:

Implementing rigorous access controls, data masking, encryption standards, and retention policies to ensure absolute compliance with SOC 2 and insurance data-privacy rules.

Skills & Experience Professional Core Experience:

3-5 years of dedicated experience operating as a Data Engineer or Database Developer managing complex, multi-source data environments (experience in high-compliance SaaS or financial services is a major plus).

Advanced SQL & Procedural Scripting:

Expert-level mastery of advanced SQL (including writing highly performant queries, complex joins, subqueries, and database optimization techniques).

Data Pipe Programming:

Solid experience writing scripts in Python or similar development languages to run automated API data extractions, cleansing routines, and custom integrations.

Modern Cloud Infrastructure:

Strong practical experience with cloud-native data services (e.g., Azure SQL, Cosmos DB, AWS Athena, or Snowflake) and cloud data pipeline engines (e.g., Azure Data Factory, dbt, or Airflow).

Relational and Dimensional Modeling:

Deep conceptual understanding of star schemas, snowflake schemas, and relational database normalization vs. denormalization strategies.

Success Metrics Data Pipeline Uptime & Delivery:

Maintain a greater than or equal to 99% success rate on scheduled ETL pipeline executions and automated data transfers.

Query Response Time Baseline:

Ensure key production databases maintain a target average query latency under 200ms for standard transactional read operations.

Data Delivery Integrity Rate:

Zero critical production incidents caused by data corruption, schema mismatches, or missing automated load steps per quarter.

Support & Reporting Team Unblocked SLA:

Resolve internally flagged database or schema pipeline blockages in an average of less than 4 hours to keep downstream business intelligence teams moving.