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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - AI & Analytics - **Company:** Computer Task Group, Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $145,600.0 - $156,000.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Data Analysis, Big Data, Cloud Computing, Cloud Database, Cloud Storage, Information Systems, Continuous Integration, Customer Data Management, Data Architecture, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Relational Databases, Software Debugging, DevOps, Digital Assets, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Enterprise Messaging Systems, Meta-Data Management, Performance Tuning, Cloud Services, Software Engineering, SQL Databases, Computational Statistics, Enterprise Data Management, Parquet, Apache Spark, Git, Data Lakes, Pyspark, Information Technology, Data Lineage, Apache Kafka, Data Management, Api Design, Stream Processing, Data Pipelines, Docker, Databricks - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/9253f17f-d7ea-4e17-b01f-698803866f27 ## About the Role * Advanced proficiency in Python and SQL for enterprise data engineering. * Experience with PySpark or comparable distributed processing frameworks. * Hands-on experience with Databricks, Apache Spark, or similar cloud data platforms. * Experience using Apache Airflow or equivalent workflow orchestration tools. * Strong knowledge of Parquet, Delta Lake, and modern analytical storage formats. * Experience building streaming solutions using Kafka or equivalent messaging platforms. * Proficiency with Docker, Git, CI/CD pipelines, and DevOps practices. * Strong understanding of cloud data architectures, API development, and distributed systems. * Knowledge of data modeling, performance tuning, and scalable data architecture design. * Familiarity with Master Data Management (MDM), data governance, data lineage, PII compliance, and responsible AI data practices. * Exposure to analytics libraries, statistical computing frameworks, and Natural Language Processing (NLP) technologies is a plus. * Excellent analytical, troubleshooting, and collaboration skills. Experience: * 5+ years of experience in data engineering, cloud data platforms, or big data development. * Demonstrated success designing enterprise-scale data platforms supporting AI, analytics, or machine learning workloads. * Experience developing robust ETL/ELT pipelines across structured, semi-structured, and streaming data sources. * Strong background in application development, API development, debugging, and performance optimization. * Experience working with modern cloud technologies and distributed computing environments. * Ability to translate complex business and technical requirements into scalable data architecture solutions. Education: * Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical discipline. * Equivalent professional experience will also be considered. Excellent verbal and written English communication skills and the ability to interact professionally with a diverse group are required. ## Description * Assess customer data environments to evaluate data quality, structure, lineage, and AI/ML readiness. * Design, build, and optimize scalable ETL/ELT pipelines across APIs, relational databases, cloud storage, files, and streaming platforms. * Develop cloud-native data infrastructure supporting enterprise AI, analytics, and machine learning initiatives. * Build high-performance batch and real-time data processing pipelines. * Create reusable, production-ready data assets for analytics, business intelligence, and machine learning teams. * Implement best practices for data governance, security, privacy, metadata management, and regulatory compliance. * Optimize data models, storage formats, and pipeline performance for large-scale processing. * Develop and maintain technical documentation, architecture diagrams, and operational procedures. * Collaborate with data scientists, software engineers, analysts, and business stakeholders to deliver scalable data solutions. * Troubleshoot and resolve complex data integration and performance challenges across modern and legacy environments. ## Related Videos - [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) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [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) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [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)