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# Senior Python Developer / Data Engineer / ML Pipelines

- **Company:** EITAcies, Inc.
- **Location:** Austin, TX, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Program Optimization, Data Cleansing, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Database Queries, Python (Programming Language), Machine Learning, Software Engineering, Workflow Management Systems, Data Processing, Feature Engineering, Large Language Models, Apache Spark, Build Management, Pyspark, Kubernetes, Apache Kafka, Machine Learning Operations, Data Pipelines
- **Published:** August 9, 2026
- **Apply:** https://www.wayup.com/i-j-Senior-Python-Developer-Data-Engineer-ML-Pipelines-Eitacies-Inc-282220073715760/

## About the Role

8+ years of software engineering experience with Python as primary language
Strong background in data engineering (ETL/ELT, pipelines, data processing)
Hands-on experience building and maintaining ML pipelines in production environments
Experience with PySpark / Apache Spark
Experience with workflow orchestration tools like Airflow, Dagster, or Prefect
Good understanding of streaming/data processing systems (Kafka, Kinesis, etc.)
Experience working with cloud platforms (AWS / GCP / Azure)
Strong SQL skills and experience with data warehouses
Comfortable working in a distributed/remote engineering setup
Plus
Experience with NLP or LLM-based systems
Familiarity with MLOps tools like MLflow, Kubeflow, or similar
Experience with feature stores
Exposure to data privacy, PII detection, or compliance-related systems

## Description

Senior Python Developer / Data Engineer / ML Pipelines
100% Remote role
Responsibilities
Design and build large-scale data pipelines for ingestion, transformation and processing
Work on ETL/ELT workflows handling different types of data
Build and maintain end-to-end ML pipelines from data preparation to deployment and monitoring
Collaborate with data scientists to productionize ML models
Work on feature engineering, training pipelines and model serving
Ensure data quality, monitoring and pipeline reliability
Optimize systems for performance, scalability and cost
Contribute to clean, maintainable, production-grade Python code


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