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# Data Engineer

- **Company:** P & A CONSULTING, INC
- **Location:** United States
- **Experience:** Expert
- **Salary:** $155,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Bash Shell, Big Data, Cloud Computing, Data Validation, Extract Transform Load (ETL), Data Vault Modeling, Data Visualization, Data Warehousing, DevOps, Python (Programming Language), Metadata, Operational Databases, Performance Tuning, Windows PowerShell, Power BI, Tableau (Software), Data Logging, Data Server Interface, Google Cloud, Azure Data Factory, Sql Optimization, Grafana, Apache Spark, Pyspark, Data Analytics, Qlikview, Star Schema, Data Management, Video Streaming, Data Pipelines
- **Published:** June 9, 2026
- **Apply:** https://www.dice.com/job-detail/de1fdb2a-0be0-4f05-b449-41216775bc88

## About the Role

Atleast 8 years of industry working experience as a data engineer

 * Advanced SQL and Python
 * Expertise in the design and construction of Big Data Lakes and Data Warehouses capable of ingesting, standardizing, and serving billions of data rows spanning diverse datasets ranging from tens to hundreds
 * Experience building dynamic, metadata driven pipelines and analyses
 * Experience maintaining and supporting production data systems, including pipeline monitoring, troubleshooting, and delivering long-term reliability and optimization enhancements
 * Building and managing fully automated data pipelines (ETL, ELT, ELTL) including:
 + Designing and building data interfaces to source systems
 + Combining and transforming data into the appropriate format for storage
 + Developing data sets for analytics purposes
 + Developing pipelines that can handle common issues/errors in a robust and automated way
 + Implementing data quality checks, observability, and cost/performance optimization
 * Cloud experience in Azure, AWS or Google Cloud Platform
 * Ability to balance enhancement work with operational responsibilities in a production environment

Preferred qualifications

 * Spark / PySpark experience highly preferable
 * Working in Agile and DevOps environments
 * Basic Python, Bash, or PowerShell for automation
 * Data modelling - Kimball, Data Vault, Star/Snowflake schema, Query-first etc.
 * Data visualisation in Power BI, Tableau, Qlik or similar
 * Architecting Data Platforms - designing BI/MI/Analytics solutions using Big Data, Relational or Streaming technologies
 * Experience with monitoring/observability tools (logging, alerting, pipeline health dashboards)
 * One or more of the following certifications:
 + Microsoft Certified: Azure Data Engineer Associate
 + AWS Certified Data Analytics - Specialty
 + Google Cloud Platform Professional Data Engineers



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