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Senior Data Developer
2 months ago
We are seeking a highly skilled Senior Data Developer to join our team at Publicis Groupe. As a key member of our data engineering team, you will be responsible for designing, developing, and supporting our Hadoop data solutions in Spark and Python (PySpark) while working with other components of the Hadoop ecosystem.
Key Responsibilities:- Design and develop innovative data solutions using PySpark, Python, and Hadoop Framework.
- Work with large volumes of data (measured in Terabytes/Billions of Transactions) and understand the challenges of transforming and enriching such datasets.
- Automate new data source integration processes to evaluate impact on existing products.
- Leverage AI/LLMs to improve data matching techniques.
- Identify opportunities to migrate solutions from On-Prem to AWS Cloud.
- Collaborate with team members, project managers, business analysts, and QA teams in conceptualizing, estimating, and developing new solutions and enhancements.
- Work closely with stakeholders to define and refine the big data platform to achieve sales, product, and strategic objectives.
- Read, extract, transform, stage, and load data to multiple targets, including Hadoop and Oracle.
- Unit testing and debugging. Perform root cause analysis (RCA) for any failed processes.
- Bachelor's Degree in Computer Science (or Engineering equivalent) or Master's with 5+ years of experience with big data ingestion, transformation, and staging using the following technologies/principles/methodologies:
- Analysis, design, and implementation experience with Hadoop distributed frameworks, including Python & Spark (SparkSQL, PySpark), HDFS, Hive, Impala, Hue, Cloudera Hadoop, Zeppelin, Jupyter, etc.
- Extensive experience with large volumes of data (measured in Terabytes/Billions of Transactions).
- AWS experience (especially related to porting solutions from On-Prem to Cloud).
- AI project work, and exposure to leveraging LLMs/Machine Learning.
- Proficient knowledge of SQL with any RDBMS.
- Familiarity with RDD and Data Frames within Spark.
- Working knowledge of data analytics.
- Working knowledge of Linux/Unix environments and comfort with Unix Shell scripts (ksh, bash).
- DevOps Knowledge is an advantage.