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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** VANTAGE AI CORPORATION - **Location:** Vienna, VA, United States - **Experience:** Expert - **Salary:** $110,000.0 - $125,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Microsoft Azure, Big Data, Business Software, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Relational Databases, Software Design Patterns, Apache Hive, Python (Programming Language), Query Optimization, Power BI, Cloud Services, SQL Stored Procedures, SQL Databases, Data Streaming, Workflow Management Systems, Scripting, Microsoft Power Automate, Azure Data Factory, Sql Optimization, Power Platform Integration, Apache Spark, Backend, Git, Data Lakes, Pyspark, Low-code, Azure Synapse Analytics, Software Version Control, Data Pipelines, Powerapps, Databricks - **Published:** July 24, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=ee377598f848d9cc ## About the Role We are seeking a Senior Data Engineer with strong hands-on expertise in the Microsoft Power Platform ecosystem and Databricks to design, build, and maintain scalable data pipelines and business applications. The ideal candidate combines deep SQL and Python engineering skills with practical experience delivering low-code/pro-code solutions on Power Apps and Power Platform, enabling both robust backend data infrastructure and front-end business tooling., * 6+ years of professional experience in data engineering or a related field * Strong hands-on experience with Databricks (Spark, Delta Lake, notebooks, job orchestration) * Proven experience building solutions with Power Apps and Power Platform (Power Automate, Power BI is a plus) * Advanced SQL skills (query optimization, stored procedures, complex joins/aggregations) * Strong Python programming skills for data engineering and scripting * Experience with cloud data platforms (Azure preferred, given Power Platform/Databricks integration) * Solid understanding of data warehousing concepts, ETL/ELT design patterns, and data modeling * Experience working with version control (Git) and CI/CD practices for data pipelines Preferred Qualifications * Experience with Azure Data Factory, Azure Synapse, or similar orchestration tools * Familiarity with Power BI for reporting/visualization * Experience with Delta Live Tables or Unity Catalog in Databricks * Knowledge of data governance, security, and compliance frameworks * Experience in an agile development environment Soft Skills * Strong problem-solving and analytical thinking * Ability to communicate technical concepts to non-technical stakeholders * Self-starter, comfortable working independently and cross-functionally, * Bachelor's (Required) Experience: * Python: 6 years (Required) * ETL: 6 years (Required) * SQL: 6 years (Required) * Databricks: 4 years (Required) ## Description * Design, develop, and maintain ETL/ELT pipelines using Databricks (PySpark/Spark SQL) for large-scale data processing * Build and support business applications, workflows, and automations using Power Apps, Power Automate, and the broader Power Platform * Write complex, performant SQL queries, stored procedures, and views across relational databases * Develop reusable Python scripts/modules for data transformation, automation, and integration tasks * Design and optimize data models and schemas to support analytics and reporting needs * Integrate Power Platform solutions with backend data sources (Databricks, SQL databases, APIs) * Collaborate with business stakeholders, analysts, and data scientists to translate requirements into technical solutions * Ensure data quality, governance, and security best practices across pipelines and applications * Monitor, troubleshoot, and optimize existing pipelines and applications for performance and reliability * Document technical designs, data flows, and processes for maintainability ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)