

TekWissen ยฎ
Lead Data Engineer
โญ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer in Bellevue, WA, for 6 months at $58/hr. Requires expertise in Databricks, Spark, Delta Lake, Snowflake, and real-time streaming. Strong programming skills in Python and SQL are essential, along with Azure ecosystem familiarity.
๐ - Country
United States
๐ฑ - Currency
$ USD
-
๐ฐ - Day rate
464
-
๐๏ธ - Date
June 13, 2026
๐ - Duration
More than 6 months
-
๐๏ธ - Location
Hybrid
-
๐ - Contract
Unknown
-
๐ - Security
Unknown
-
๐ - Location detailed
Bellevue, WA
-
๐ง - Skills detailed
#BI (Business Intelligence) #Data Engineering #Data Pipeline #Spark (Apache Spark) #Azure Event Hubs #Kafka (Apache Kafka) #Metadata #Programming #Azure #Data Quality #Data Layers #Leadership #SQL (Structured Query Language) #"ACID (Atomicity #Consistency #Isolation #Durability)" #Snowflake #Storage #Semantic Models #Monitoring #Data Governance #"ETL (Extract #Transform #Load)" #Data Modeling #Delta Lake #Batch #Indexing #Data Warehouse #ADLS (Azure Data Lake Storage) #Microsoft Power BI #Cloud #Datasets #Databricks #ADF (Azure Data Factory) #Observability #Python #Scala #DevOps #Data Storage #MDM (Master Data Management)
Role description
Position: Lead Data Engineer
Location: Bellevue, WA
Duration: 6 Months
Work Type: Hybrid
Payrate:$ 58.00 - 58.00/hr.
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Job Description:
โข 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.
โข This role will provide technical leadership and drive end-to-end data engineering architecture and delivery.
Key Responsibilities:
โข Architecture & Platform Design Design and implement end-to-end data platform architecture (ingestion processing storage serving)
โข 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
โข 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
โข Design and implement real-time pipelines using Kafka / Azure Event Hubs Ensure data freshness within ~15-minute SLA
โข Enable incremental processing and efficient data updates Data Quality & Governance Establish data quality frameworks (validation, completeness, consistency checks) Implement monitoring, alerting, and data observability
โข 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
โข Ensure consistent, accurate, and high-performance reporting Performance & Scalability Optimize pipelines and storage for large-scale datasets (TB/PB)
โข 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:
โข Strong experience in data engineering and platform architecture (Lead level)
โข Expertise in: Databricks, Spark, Delta Lake Snowflake or similar cloud data warehouses Hands-on with streaming technologies (Kafka / Event Hubs)
โข Strong knowledge of data modeling, ETL/ELT, and pipeline design Experience with data quality frameworks and monitoring tools
โข Familiarity with Power BI / Microsoft Fabric Strong programming skills (Python, SQL) Experience with Azure ecosystem (ADF, ADLS, AKS - preferred)
โข Nice to Have Experience with real-time analytics platforms Exposure to data governance / MDM frameworks
โข Familiarity with CI/CD and DevOps practices for data platforms
Key Expectations:
โข Own and deliver a robust, scalable data platform
โข Ensure high data quality and near real-time availability (15 min SLA) Drive standardization, reusability, and performance optimization
โข Enable business-ready, trusted data for analytics and decision-making
โข 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.
TekWissenยฎ Group is an equal opportunity employer supporting workforce diversity.
Position: Lead Data Engineer
Location: Bellevue, WA
Duration: 6 Months
Work Type: Hybrid
Payrate:$ 58.00 - 58.00/hr.
Overview:
TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation, information technology and services
Job Description:
โข 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.
โข This role will provide technical leadership and drive end-to-end data engineering architecture and delivery.
Key Responsibilities:
โข Architecture & Platform Design Design and implement end-to-end data platform architecture (ingestion processing storage serving)
โข 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
โข 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
โข Design and implement real-time pipelines using Kafka / Azure Event Hubs Ensure data freshness within ~15-minute SLA
โข Enable incremental processing and efficient data updates Data Quality & Governance Establish data quality frameworks (validation, completeness, consistency checks) Implement monitoring, alerting, and data observability
โข 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
โข Ensure consistent, accurate, and high-performance reporting Performance & Scalability Optimize pipelines and storage for large-scale datasets (TB/PB)
โข 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:
โข Strong experience in data engineering and platform architecture (Lead level)
โข Expertise in: Databricks, Spark, Delta Lake Snowflake or similar cloud data warehouses Hands-on with streaming technologies (Kafka / Event Hubs)
โข Strong knowledge of data modeling, ETL/ELT, and pipeline design Experience with data quality frameworks and monitoring tools
โข Familiarity with Power BI / Microsoft Fabric Strong programming skills (Python, SQL) Experience with Azure ecosystem (ADF, ADLS, AKS - preferred)
โข Nice to Have Experience with real-time analytics platforms Exposure to data governance / MDM frameworks
โข Familiarity with CI/CD and DevOps practices for data platforms
Key Expectations:
โข Own and deliver a robust, scalable data platform
โข Ensure high data quality and near real-time availability (15 min SLA) Drive standardization, reusability, and performance optimization
โข Enable business-ready, trusted data for analytics and decision-making
โข 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.
TekWissenยฎ Group is an equal opportunity employer supporting workforce diversity.






