Data Engineer Mid

The Intersect Group; Irving (TX); Hybrid; USD 90,000 - 140,000; Part time

Job summary

The Intersect Group is hiring a Data Engineer (Mid) in Irving, TX, offering hybrid work. This role focuses on building modern data platforms and AI-enabled solutions, integrating enterprise data with AI insights and delivering scalable data products.

You will own data engineering components from development to production, collaborating with AI/ML engineers, data scientists, and stakeholders to meet business needs and ensure data quality and accessibility.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or a related quantitative field, or equivalent practical experience.
• 3–5 years of data engineering or related software engineering experience.
• Proficiency with Python and SQL, including complex queries and performance tuning.
• Experience with Spark/PySpark and distributed data processing.

Responsibilities

• Build, maintain, and optimize scalable batch and near real-time data pipelines.
• Integrate data from enterprise applications, APIs, event streams, and AI outputs into analysts-ready datasets.
• Develop transformations across structured and semi-structured data with time zones and deduplication.
• Create data models and curated datasets for analytics and AI workflows.
• Collaborate with AI/ML teams to support inference and model outputs.
• Implement data quality checks, reconciliation, monitoring, and alerting.
• Troubleshoot pipeline failures and implement retries, backfills, and incremental processing.
• Partner with product managers and engineers to translate business needs into data solutions.

Skills

Python

SQL

Spark

Cloud (Azure/AWS)

ETL/ELT

Data modeling

Airflow/Databricks

Git

CI/CD

Testing

Education

Bachelor's degree in Computer Science or related field

Tools

Databricks

Delta Lake

Kafka

Azure Event Hubs

Terraform

Kubernetes

CI/CD tooling

Job description

## Data Engineer Mid**Irving,TX75063**Posted: 11/06/2026Employment Type:ContractCategory: IT - BI/DA - Developer/EngineerJob Number: 251429Work Location: Hybrid## Job DescriptionData Engineer (Mid)Overview 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. Key Responsibilities* 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.Required Qualifications* 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.