We are seeking a Senior Data Engineer to develop and maintain scalable data pipelines using Python and PySpark. The ideal candidate will have experience with Big Data Technologies, Databases, and Cloud Platforms. This role requires strong technical skills and collaboration with teams on cloud deployments, CI/CD, and production support.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
Data Engineer ($80-85K+ Benefits) + H1b Transfers are Workable
Dallas, TX
Fulltime (Permanent)
5 Positions
Job Description:
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Experience: 5 Years
Core Skills:
- Data Engineering: Data Pipelines, Data Processing, ETL, Large-Scale Data Processing
- Big Data Technologies: Python, PySpark, Apache Spark, Databricks, Delta Lake
- Databases: PostgreSQL, MongoDB, Redis, SQL, NoSQL
- Streaming & Real-Time Processing: Kafka, Kafka Streaming, Real-Time Data Processing
- Cloud Platforms: Azure, AWS, Cloud Data Services
- Performance Optimization: Data Partitioning, Performance Tuning, In-Memory Optimization
- DevOps & Deployment: CI/CD Pipelines, Production Deployment, Linux, Unix
- APIs & Architecture: REST APIs, Application Development, System Design, Software Architecture
- Platform & Security: Multi-User Data Platforms, Access Management
- GenAI & AI Concepts: LLM Workflows, Prompt Versioning, Evaluation Frameworks
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Key Responsibilities:
- Develop and maintain scalable data pipelines using Python and PySpark.
- Work with Databricks and Delta Lake for data processing and optimization.
- Design and manage SQL/NoSQL database integrations and workflows.
- Support real-time streaming solutions using Kafka or similar frameworks.
- Optimize data processing performance and partitioning strategies.
- Collaborate with teams on cloud deployments, CI/CD, and production support.
- Integrate REST APIs and support application-level data requirements.
- Contribute to GenAI and LLM-based workflow initiatives where applicable.
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