> Markdown version of [/jobs/ext/269374-data-engineer](https://www.wearedevelopers.com/jobs/ext/269374-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** MatchPoint Solutions - **Location:** Maryland Heights, MO, United States (Remote available) - **Experience:** Experienced - **Salary:** $135,200.0 - $145,600.0 - **Contract:** Temporary contract - **Skills:** Microsoft Azure, Code Review, Continuous Integration, Data Cleansing, Data Deduplication, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Database Queries, Distributed Computing Environment, Integrated Development Environments, Python (Programming Language), Query Optimization, Azure Data Lake, SQL Databases, Data Streaming, Data Logging, Azure Data Factory, Apache Spark, Backend, Git, Pyspark, Infrastructure Automation Frameworks, Data Lineage, Bicep, Real Time Data, Terraform, Azure Synapse Analytics, Software Version Control, Data Pipelines, Serverless Computing, Databricks - **Published:** May 27, 2026 - **Apply:** https://www.careerjet.com/jobad/uscd18903c40f02320eea43ab827539bee ## About the Role * 4+ years of professional experience as a Data Engineer with a strong Azure focus. * Databricks + Medallion Architecture: hands-on experience designing and implementing ingestion layers using the Medallion Architecture (Bronze/Silver/Gold) within Azure Databricks, including Delta Live Tables or structured notebook workflows. * Python / PySpark Notebooks: primary development environment for pipeline and transformation logic; strong command of PySpark for distributed data processing and Python for utility scripting and orchestration. * Azure Data Services - Synapse, Delta Tables, Unity Catalog: demonstrable experience with Azure Synapse Analytics (SQL and Spark pools), Delta table management (schema evolution, VACUUM, OPTIMIZE), and Unity Catalog for governance and lineage. These are named source systems on this engagement. * ETL/ELT Pipeline Development: proven track record building robust cleaning, deduplication, and multi-source transformation pipelines that handle messy, real-world enterprise data at scale. * Azure DevOps (ADO): use of ADO for Git-based source control, pull request workflows, and CI/CD pipeline deployment of Databricks jobs and ADF pipelines. * Solid experience with Azure Data Factory for orchestrating complex data pipelines. * Strong SQL skills including complex query optimisation. Desirable Skills * Microsoft Certified: Azure Data Engineer Associate (DP-203) certification. * Familiarity with infrastructure-as-code tools (Terraform, Bicep) for Azure resource deployment. * Experience with data cataloguing and governance using Microsoft Purview. * Knowledge of streaming architectures and near-real-time data ingestion patterns. Personal Attributes * Detail-oriented with a strong commitment to data quality and pipeline reliability. * Proactive self-starter able to operate with a high degree of autonomy. * Strong collaborator with the ability to align engineering decisions to data science and business requirements. * Comfortable navigating ambiguity and adapting to evolving project needs. ## Description We are looking for an experienced Data Engineer to build and maintain robust, scalable data infrastructure for a high-priority customer project. You will architect and deliver the data pipelines that power data science model development and business intelligence, working closely with the Data Scientists and Backend Developer to ensure reliable, high-quality data flows across the Azure ecosystem., * Design, build, and maintain production-grade data pipelines ingesting data from multiple enterprise source systems into Azure Databricks and Azure Synapse Analytics. * Implement and manage the Medallion Architecture (Bronze, Silver, Gold layers) within Databricks to ensure structured, traceable data progression from raw ingestion to analytics-ready datasets. * Develop ELT/ETL workflows using Azure Data Factory, Databricks Notebooks, and PySpark - including data cleaning, deduplication, and transformation logic. * Build and optimize end-to-end data pipelines to prepare clean, feature-engineered datasets for modelling. * Architect and manage Delta tables within Databricks, enforcing schema evolution, time travel, and data quality constraints. * Administer and leverage Unity Catalog for data governance, access control, and lineage tracking across all ingested datasets. * Configure and manage Azure Data Lake Storage Gen2 (ADLS Gen2) as the central data repository. * Collaborate with Data Scientists to optimise data schemas and provide clean, feature-ready datasets for modelling. * Develop and maintain data models within Azure Synapse Analytics (dedicated and serverless SQL pools). * Use Azure DevOps (ADO) for source control, CI/CD pipeline management, and collaborative code review on all pipeline assets. * Implement monitoring, alerting, and logging for all data pipeline processes to ensure operational reliability. * Apply data security, governance, and compliance best practices aligned to Unity Catalog and customer requirements. ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [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) - [Back(end) to the Future: Embracing the continuous Evolution of Infrastructure and Code](https://www.wearedevelopers.com/videos/440-back-end-to-the-future-embracing-the-continuous-evolution-of-infrastructure-and-code) - [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) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs)