Lead Data Engineer
Job Location:
Job Location:
Bellevue, WA - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
26 days ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Lead Data Engineer
Frisco TX - Bellevue WA
Data Platform & Near Real-Time Analytics Role Overview We are seeking a Lead Data Engineer to design and build a scalable high-quality data platform that ingests data from multiple sources ensures data quality and governance and delivers near real-time insights (15-minute SLA) through Power BI / Microsoft Fabric dashboards.
This role will provide technical leadership and drive end-to-end data engineering architecture and delivery.
Key Responsibilities
Architecture & Platform Design Design and implement end-to-end data platform architecture (ingestion processing storage serving)
Define batch and near real-time data pipelines ensuring low-latency and high reliability Make technology decisions across Databricks Delta Lake Snowflake and Azure ecosystem
Data Engineering & Pipelines Build scalable pipelines using: Databricks / Spark for large-scale processing Delta Lake for ACID-compliant data storage Snowflake for data warehousing and analytics Implement ETL/ELT pipelines with strong data modeling practices Streaming & Real-Time Processing
Design and implement real-time pipelines using Kafka / Azure Event Hubs Ensure data freshness within 15-minute SLA
Enable incremental processing and efficient data updates Data Quality & Governance Establish data quality frameworks (validation completeness consistency checks) Implement monitoring alerting and data observability
Define and enforce data governance lineage and metadata standards Data Serving & Analytics Enable optimized data layers for Power BI / Microsoft Fabric dashboards Design semantic models and curated data layers for business consumption
Ensure consistent accurate and high-performance reporting Performance & Scalability Optimize pipelines and storage for large-scale datasets (TB/PB)
Ensure low-latency query performance and efficient compute usage Implement partitioning indexing caching and optimization strategies Leadership & Collaboration Lead and mentor a team of data engineers Collaborate with Technical Product Managers BI teams and business stakeholders Drive best practices in coding architecture and delivery Manage technical risks dependencies and roadmap execution
Required Skills
Strong experience in data engineering and platform architecture (Lead level)
Expertise in: Databricks Spark Delta Lake Snowflake or similar cloud data warehouses Hands-on with streaming technologies (Kafka / Event Hubs)
Strong knowledge of data modeling ETL/ELT and pipeline design Experience with data quality frameworks and monitoring tools
Familiarity with Power BI / Microsoft Fabric Strong programming skills (Python SQL) Experience with Azure ecosystem (ADF ADLS AKS - preferred)
Nice to Have Experience with real-time analytics platforms Exposure to data governance / MDM frameworks
Familiarity with CI/CD and DevOps practices for data platforms
Key Expectations
Own and deliver a robust scalable data platform
Ensure high data quality and near real-time availability (15 min SLA) Drive standardization reusability and performance optimization
Enable business-ready trusted data for analytics and decision-making
Business Impact Build and scale a modern data platform that delivers trusted near real-time insights enabling faster decisions and powering analytics across the organization.
Data Platform & Near Real-Time Analytics Role Overview We are seeking a Lead Data Engineer to design and build a scalable high-quality data platform that ingests data from multiple sources ensures data quality and governance and delivers near real-time insights (15-minute SLA) through Power BI / Microsoft Fabric dashboards.
This role will provide technical leadership and drive end-to-end data engineering architecture and delivery.
Key Responsibilities
Architecture & Platform Design Design and implement end-to-end data platform architecture (ingestion processing storage serving)
Define batch and near real-time data pipelines ensuring low-latency and high reliability Make technology decisions across Databricks Delta Lake Snowflake and Azure ecosystem
Data Engineering & Pipelines Build scalable pipelines using: Databricks / Spark for large-scale processing Delta Lake for ACID-compliant data storage Snowflake for data warehousing and analytics Implement ETL/ELT pipelines with strong data modeling practices Streaming & Real-Time Processing
Design and implement real-time pipelines using Kafka / Azure Event Hubs Ensure data freshness within 15-minute SLA
Enable incremental processing and efficient data updates Data Quality & Governance Establish data quality frameworks (validation completeness consistency checks) Implement monitoring alerting and data observability
Define and enforce data governance lineage and metadata standards Data Serving & Analytics Enable optimized data layers for Power BI / Microsoft Fabric dashboards Design semantic models and curated data layers for business consumption
Ensure consistent accurate and high-performance reporting Performance & Scalability Optimize pipelines and storage for large-scale datasets (TB/PB)
Ensure low-latency query performance and efficient compute usage Implement partitioning indexing caching and optimization strategies Leadership & Collaboration Lead and mentor a team of data engineers Collaborate with Technical Product Managers BI teams and business stakeholders Drive best practices in coding architecture and delivery Manage technical risks dependencies and roadmap execution
Required Skills
Strong experience in data engineering and platform architecture (Lead level)
Expertise in: Databricks Spark Delta Lake Snowflake or similar cloud data warehouses Hands-on with streaming technologies (Kafka / Event Hubs)
Strong knowledge of data modeling ETL/ELT and pipeline design Experience with data quality frameworks and monitoring tools
Familiarity with Power BI / Microsoft Fabric Strong programming skills (Python SQL) Experience with Azure ecosystem (ADF ADLS AKS - preferred)
Nice to Have Experience with real-time analytics platforms Exposure to data governance / MDM frameworks
Familiarity with CI/CD and DevOps practices for data platforms
Key Expectations
Own and deliver a robust scalable data platform
Ensure high data quality and near real-time availability (15 min SLA) Drive standardization reusability and performance optimization
Enable business-ready trusted data for analytics and decision-making
Business Impact Build and scale a modern data platform that delivers trusted near real-time insights enabling faster decisions and powering analytics across the organization.
