Mastech Digital
Business Intelligence Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Business Intelligence Engineer contract position in Seattle/Redmond, WA, requiring 5+ years of experience, strong SQL and Python skills, AWS expertise, and proficiency in BI tools. A Bachelor’s degree in a related field is mandatory.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 20, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Seattle, WA
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🧠 - Skills detailed
#Data Ingestion #Apache Iceberg #Amazon QuickSight #Data Engineering #Datasets #Spark (Apache Spark) #Scala #Microsoft Power BI #Data Mart #Cloud #S3 (Amazon Simple Storage Service) #Visualization #Data Modeling #SQL Server #Computer Science #Redshift #Python #Data Integrity #Leadership #ML (Machine Learning) #Airflow #Trend Analysis #SQL (Structured Query Language) #AWS (Amazon Web Services) #Trino #AWS Glue #Databases #Forecasting #Regression #Lambda (AWS Lambda) #MySQL #Data Science #Aurora #A/B Testing #Tableau #Athena #Automation #BI (Business Intelligence) #Data Lake #"ETL (Extract #Transform #Load)" #Oracle
Role description
Job Description – Business Intelligence Engineer
Location: Seattle/Redmond, WA (Onsite)
Job Type: Contract
Key Responsibilities
Design, develop, and maintain scalable ETL pipelines processing large-scale transactional datasets using SQL, Python, Spark, and AWS technologies.
Build and optimize data models, data marts, and automated reporting frameworks for business and operational analytics.
Develop executive-level dashboards and reporting solutions using Amazon QuickSight, Tableau, or Power BI to support strategic decision-making.
Perform deep-dive root cause analysis, trend analysis, and data validation across high-volume data environments.
Implement and maintain automated data ingestion pipelines using AWS Glue, Lambda, Athena, S3, Redshift, and related cloud services.
Work with cross-functional teams including Product Managers, Engineering, Finance, and Operations to define KPIs and deliver actionable insights.
Conduct statistical analysis and data science initiatives including A/B testing, regression analysis, segmentation modeling, and forecasting.
Ensure data integrity, consistency, and quality across multiple data sources and enterprise systems.
Optimize query performance and improve reporting efficiency for large-scale distributed datasets.
Support executive business reviews by developing automated metrics reporting and business performance dashboards.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Business Analytics, Accounting, or related field.
5+ years of experience in Business Intelligence Engineering, Data Engineering, or Analytics.
Strong hands-on experience with SQL and Python in large-scale data environments.
Experience building ETL/ELT pipelines and managing high-volume datasets (billions of records).
Expertise with AWS services including Redshift, S3, Athena, Glue, Lambda, EMR, and QuickSight.
Strong experience with BI and visualization tools such as Tableau, Power BI, or QuickSight.
Experience with data modeling, reporting automation, and dashboard development.
Knowledge of statistical analysis techniques including regression models, A/B testing, and segmentation analysis.
Ability to work onsite in Seattle/Redmond, WA.
Strong communication and stakeholder management skills with experience supporting VP/L10 leadership reporting.
Preferred Qualifications
Experience with Apache Iceberg, Airflow, Spark, or Trino.
Experience working in tech, cloud infrastructure, advertising, or finance domains.
Familiarity with machine learning concepts and predictive analytics.
Experience optimizing distributed querying and cloud data lake architectures.
Prior experience supporting operational analytics and executive business reviews.
Technical Skills
Languages: SQL, Python, Spark
Cloud & Databases: AWS, Redshift, Athena, S3, Aurora, MySQL, Oracle, SQL Server, EMR
Visualization Tools: Tableau, Power BI, QuickSight
Data Engineering Tools: Glue, Lambda, Airflow, EventBridge
Analytics & Data Science: A/B Testing, Regression Models, Bayesian Analysis, Decision Trees, Random Forests
Job Description – Business Intelligence Engineer
Location: Seattle/Redmond, WA (Onsite)
Job Type: Contract
Key Responsibilities
Design, develop, and maintain scalable ETL pipelines processing large-scale transactional datasets using SQL, Python, Spark, and AWS technologies.
Build and optimize data models, data marts, and automated reporting frameworks for business and operational analytics.
Develop executive-level dashboards and reporting solutions using Amazon QuickSight, Tableau, or Power BI to support strategic decision-making.
Perform deep-dive root cause analysis, trend analysis, and data validation across high-volume data environments.
Implement and maintain automated data ingestion pipelines using AWS Glue, Lambda, Athena, S3, Redshift, and related cloud services.
Work with cross-functional teams including Product Managers, Engineering, Finance, and Operations to define KPIs and deliver actionable insights.
Conduct statistical analysis and data science initiatives including A/B testing, regression analysis, segmentation modeling, and forecasting.
Ensure data integrity, consistency, and quality across multiple data sources and enterprise systems.
Optimize query performance and improve reporting efficiency for large-scale distributed datasets.
Support executive business reviews by developing automated metrics reporting and business performance dashboards.
Required Qualifications
Bachelor’s degree in Computer Science, Information Systems, Business Analytics, Accounting, or related field.
5+ years of experience in Business Intelligence Engineering, Data Engineering, or Analytics.
Strong hands-on experience with SQL and Python in large-scale data environments.
Experience building ETL/ELT pipelines and managing high-volume datasets (billions of records).
Expertise with AWS services including Redshift, S3, Athena, Glue, Lambda, EMR, and QuickSight.
Strong experience with BI and visualization tools such as Tableau, Power BI, or QuickSight.
Experience with data modeling, reporting automation, and dashboard development.
Knowledge of statistical analysis techniques including regression models, A/B testing, and segmentation analysis.
Ability to work onsite in Seattle/Redmond, WA.
Strong communication and stakeholder management skills with experience supporting VP/L10 leadership reporting.
Preferred Qualifications
Experience with Apache Iceberg, Airflow, Spark, or Trino.
Experience working in tech, cloud infrastructure, advertising, or finance domains.
Familiarity with machine learning concepts and predictive analytics.
Experience optimizing distributed querying and cloud data lake architectures.
Prior experience supporting operational analytics and executive business reviews.
Technical Skills
Languages: SQL, Python, Spark
Cloud & Databases: AWS, Redshift, Athena, S3, Aurora, MySQL, Oracle, SQL Server, EMR
Visualization Tools: Tableau, Power BI, QuickSight
Data Engineering Tools: Glue, Lambda, Airflow, EventBridge
Analytics & Data Science: A/B Testing, Regression Models, Bayesian Analysis, Decision Trees, Random Forests
