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Etl Pipeline Data Jobs

3 jobs found

1mo ago

Data Engineer with Python and SQL

Realign LLC Charlotte, NC

Charlotte, NC

1mo ago Closed

$119k+/yr Full time Backend Developer Python Apache Solr

This position is no longer accepting applications (closed Oct 23, 2026).

Job Description

Realign LLC is hiring a data engineer in Charlotte, NC with an onsite focus on building cloud-native data platforms and high-throughput pipelines.

Responsibilities

Design and build large-scale data pipelines using Python
Develop and support data ingestion, processing, indexing, and retrieval for structured and unstructured data
Lead the architecture of cloud-native data lakes and data warehouses
Optimize big data processing jobs to improve speed and cost
Mentor junior data engineers and conduct code reviews
Implement data governance, data quality, and monitoring systems
Partner with data scientists to deploy machine learning models

Requirements

8+ years of relevant experience
Bachelor’s or master’s degree in computer science or a related field
Primary skills:
- Python, SQL
- Data ingestion and ETL
- API development and integration
- Mongo DB
- Oracle or relational databases
- Elastic or Solr search
- Vector database
- Linux/Bash
- OpenShift containers
- Git, Jenkins
- CI/CD and data modelling
Secondary:
- FastAPI
- Data quality and validation
- Performance tuning
Required skills:
- Data / Python Engineer (Python) / DevOps Engineer

Technology Stack

Python, SQL
Mongo DB, Oracle, Relational Databases
Elastic, Solr
Vector Database
Linux/Bash, OpenShift containers
Git, Jenkins, CI/CD
Data modelling, FastAPI

Location: Charlotte, NC (onsite)

Compensation: USD 119,000 per year

Experience level: 8+ years

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1mo ago

AI & Data Engineer

EVERFORCE LLC Santa Clara, CA

Santa Clara, CA

1mo ago Closed

$110k - $150k/yr Full time Ai Engineering Ai Ml Api Integration

This position is no longer accepting applications (closed Oct 19, 2026).

Job Description

The AI & Data Engineer at EVERFORCE LLC will help build and operate the data and AI foundation behind enterprise initiatives. This onsite role in Santa Clara, CA focuses on scalable pipeline engineering, end-to-end AI/ML model development, and practical integration with enterprise systems and cloud platforms. The position spans ingestion, transformation, deployment, monitoring, and the governance artifacts needed to keep solutions transparent and audit-ready.

You will work across ETL/ELT and machine learning workflows, including scenarios involving large language models, prompt engineering, and retrieval-augmented generation (RAG) pipelines.

What You’ll Do

Design, build, and maintain scalable data pipelines and ETL/ELT processes to ingest, clean, transform, and integrate both structured and unstructured data from enterprise systems and other sources.
Develop, train, test, and deploy machine learning and artificial intelligence models, including (when applicable) integration of large language models (LLMs), prompt engineering, and retrieval-augmented generation (RAG) pipelines.
Integrate AI/ML models and data pipelines with enterprise applications, APIs, and cloud-based platforms.
Monitor and troubleshoot pipeline and model performance, focusing on data validation, issue resolution, and continuous optimization of quality, reliability, and effectiveness.
Maintain documentation, metadata, and data lineage to support governance, transparency, and auditability.
Collaborate with IT, data science, and business teams to gather requirements, refine solutions, and support ongoing AI and data initiatives.

Key Technologies

ETL/ELT
Machine learning
Artificial intelligence
Large language models (LLMs)
Prompt engineering
Retrieval-augmented generation (RAG)
APIs
Cloud-based platforms

Deliverables

Documented, production-ready data pipelines and ETL/ELT jobs, including source-to-target mapping and data quality checks.
Trained, validated, and deployed AI/ML models (or model enhancements), along with relevant performance and evaluation metrics.
Integrations connecting AI/ML models and data pipelines to enterprise systems, applications, and/or cloud platforms.
Dashboards, reports, or monitoring tools to track data quality, pipeline health, and/or model performance.
Technical documentation covering data pipeline architecture, data lineage, model design, and deployment processes.
Periodic status updates and knowledge-transfer materials for IT and business teams.

Location: Santa Clara, CA (onsite)
Compensation: USD 110,000 - 150,000 per year
Experience: 2 years minimum

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1mo ago

AI Engineer

Chase Robotics and Ai Rocklin, CA

Rocklin, CA

1mo ago Closed

Up to $200k/yr Full time Ai Ml Artificial Intelligence Big Data

This position is no longer accepting applications (closed Sep 27, 2026).

Job Description

Build and deploy advanced AI while working in a hybrid setup in Rocklin, CA. This AI Engineer role at Chase Robotics and Ai focuses on designing, building, and putting machine learning into production, from scalable data systems to robust cloud deployments.

What you’ll do

Develop, train, and evaluate machine learning models using frameworks such as TensorFlow, with an emphasis on accuracy and efficiency across diverse applications.
Design and implement scalable big data systems using tools including Hadoop and Spark, along with ETL processes for managing large datasets effectively.
Apply statistical modeling and analysis with R, SAS, and statistical analysis software to derive meaningful insights from complex data.
Integrate AI models into production environments using model deployment strategies that support robustness and scalability across cloud platforms such as AWS.
Collaborate with cross-functional teams to build NLP applications and generative AI solutions aimed at improving user engagement.
Run model training sessions for predictive modeling, including model evaluation and continuous improvement cycles.
Use SQL databases, data mining techniques, and database design principles to optimize data storage and retrieval for analytics use cases.

What you bring

Proven experience in machine learning/AI-based analysis, including strong understanding of AI implementation in real-world scenarios.
Hands-on expertise with machine learning frameworks such as TensorFlow and Spark MLlib (or similar tools).
Familiarity with big data systems and the Hadoop ecosystem, including HDFS and MapReduce, plus Spark for large-scale data processing.
Programming experience in Python, Java, C, VBA, and Bash (Unix shell), with additional knowledge of SQL for database management.
Experience with cloud-based machine learning services on AWS (or similar providers) is highly desirable.
Knowledge of NLP, predictive modeling analysis, statistical analysis tools, and model evaluation techniques.
Understanding of data analytics workflows, including data mining, data integration with Talend, visualization with Looker, and considerations for data scalability.

Compensation: USD 200,000 per year.

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