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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer Mid - **Company:** AI Enabled Solutions LLC - **Location:** Irving, TX, United States - **Experience:** Experienced - **Contract:** Contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Code Review, Information Systems, Continuous Integration, Data Validation, Data Deduplication, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Systems, Data Warehousing, Relational Databases, Database Queries, Distributed Computing Environment, Monitoring of Systems, Python (Programming Language), Machine Learning, AI-enabled Products, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Data Server Interface, Enterprise Software Applications, Apache Spark, Git, Containerization, Data Lakes, Pyspark, Semi-structured Data, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Deployment Automation, Bicep, Apache Kafka, Operational Systems, Spark Streaming, Data Management, Video Streaming, Model Inference, Terraform, Data Pipelines, Docker, Databricks - **Published:** November 7, 2026 - **Apply:** https://www.dice.com/job-detail/2dfc8847-9420-4229-9d66-0086196eda30 ## About the Role * Bachelor's degree in Computer Science, Software Engineering, Information Systems, Engineering, Mathematics, Statistics, or a related quantitative discipline, or equivalent practical experience. * 3-5 years of experience in data engineering or a closely related software engineering role. * Strong hands-on proficiency with Python and SQL, including complex queries, transformations, optimization, and troubleshooting. * Experience with Spark/PySpark and distributed data processing frameworks. * Experience designing, building, and supporting ETL/ELT pipelines on cloud platforms such as Azure or AWS. * Understanding of data modeling, relational databases, data lakes, data warehouses, and incremental processing patterns. * Experience with workflow orchestration tools such as Apache Airflow or Databricks Workflows. * Familiarity with event-driven and streaming data processing concepts including event time management, deduplication, and reliable delivery. * Experience with Git, automated testing frameworks, monitoring tools, and production support. * Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders. Preferred Qualifications * Hands-on experience with Databricks, Delta Lake, or lakehouse architectures. * Experience with Databricks Asset Bundles (DABs) or similar deployment automation frameworks supporting CI/CD processes. * Experience with streaming technologies such as Kafka, Azure Event Hubs, or Spark Structured Streaming. * Experience working with customer, inventory, operational, financial, or transactional datasets. * Experience preparing datasets for machine learning, anomaly detection, predictive analytics, or AI model evaluation. * Familiarity with multimodal data, unstructured data processing, and time-based event correlation. * Exposure to edge-to-cloud integration patterns, containerized workloads, Kubernetes, Docker, or infrastructure-as-code tools such as Terraform or Bicep. ## Description We are seeking a mid-level Data Engineer to join a growing Enterprise AI team. This team is focused on building modern data platforms and AI-enabled solutions that drive business value, operational efficiency, and informed decision-making. If you enjoy solving complex data challenges, building scalable data products, and working at the intersection of data engineering and AI, this is an excellent opportunity to make a meaningful impact. About the Role You will join a multidisciplinary team of data engineers, AI/ML engineers, data scientists, and product stakeholders building enterprise data and AI solutions. In this role, you will build reliable data foundations that power AI-enabled products, operational intelligence, and business decision-making. You'll integrate enterprise data with AI-generated insights and contribute reusable data capabilities across a variety of AI and analytics initiatives. This is a hands-on individual contributor role. You'll own well-defined data engineering components from development through production, partnering with senior engineers and architects on solution design and technical direction., * Build, maintain, and enhance scalable batch and near real-time data pipelines using Python, SQL, and Spark/PySpark. * Integrate data from enterprise applications, operational systems, APIs, event streams, and AI inference outputs into reliable, analysis-ready datasets. * Develop transformations that combine structured and semi-structured data across sources using consistent identifiers and timestamps, including handling time zones, duplicate records, and late-arriving events. * Create and maintain data models and curated datasets for business analytics, AI model development and evaluation, and AI-enabled application workflows. * Partner with AI/ML engineers to deliver data interfaces for inference workflows and capture model outputs, confidence scores, and user feedback to support continuous improvement. * Implement data quality checks, reconciliation processes, monitoring, and alerting to ensure completeness, accuracy, freshness, and traceability. * Troubleshoot pipeline failures and performance issues while implementing reliable retries, backfills, and incremental processing strategies. * Collaborate with product managers, data scientists, analysts, and engineering partners to translate business requirements into practical data solutions. * Follow data security, privacy, governance, access control, and retention requirements when handling enterprise and AI-generated data. * Write maintainable, tested code and participate in code reviews, CI/CD practices, and documentation of schemas, data lineage, dependencies, and operational procedures.