Direct Client:: W2 Position:: Need Hadoop & Python ETL Developer (Spark + Cloud + Snowflake ELT) :: Jacksonville, FL (Hybrid)

W2 contract to Fulltime position

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Job Title: Hadoop & Python ETL Developer (Spark + Cloud + Snowflake ELT)

Location: Jacksonville, FL (Hybrid)

Job Description:

We are seeking a highly skilled Hadoop & Python ETL Developer to design, build, and optimize scalable data pipelines supporting big data processing and cloud-based analytics platforms. The role focuses on leveraging Apache Spark, Python, and Snowflake ELT to enable efficient data ingestion, transformation, and delivery across enterprise systems. The ideal candidate will have strong experience in distributed data processing, cloud ecosystems, and modern data warehousing practices.

Roles & Responsibilities:

• Design and develop scalable ETL/ELT pipelines using Python and Apache Spark.
• Build and maintain big data solutions using Hadoop ecosystem tools (HDFS, Hive, YARN).
• Develop data ingestion frameworks for batch and near real-time processing.
• Implement ELT processes in Snowflake, including data modeling, transformations, and performance tuning.
• Integrate data from multiple sources (APIs, databases, flat files, streaming platforms).
• Optimize Spark jobs for performance, scalability, and cost efficiency.
• Work with cloud platforms (AWS / Azure / Google Cloud Platform) for data storage, processing, and orchestration.
• Develop reusable data processing components and frameworks.
• Ensure data quality, validation, and governance across pipelines.
• Collaborate with data architects, analysts, and business stakeholders to understand requirements.
• Monitor and troubleshoot data pipelines and production issues.
• Implement CI/CD pipelines for data engineering workflows.
• Support migration from legacy systems to cloud-based data platforms.

Required Skills:

• Strong programming experience in Python for ETL development.
• Hands-on experience with Apache Spark (PySpark / Spark SQL).
• Solid understanding of Hadoop ecosystem (HDFS, Hive, MapReduce concepts).
• Experience with Snowflake (ELT, SnowSQL, Streams, Tasks, performance tuning).
• Expertise in SQL and data modeling (dimensional modeling, star/snowflake schema).
• Experience with cloud platforms (AWS / Azure / Google Cloud Platform) and related data services.
• Familiarity with orchestration tools (Airflow, Control-M, or similar).
• Knowledge of data formats: JSON, Parquet, Avro, ORC.
• Experience with version control systems (Git) and CI/CD pipelines.
• Understanding of distributed computing and parallel processing.