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Job Overview : Qualifications :

- Master’s / Engineering Degree with 0- 2 years of experience in Big Data systems, Hive, Hadoop, Spark (Python/ scala) and cloud-based data management technologies
- Hands-on experience in Unix Scripting, Python and Scala programing along with strong experience in SQL.
- Comfortable working with completed unstructured, undocumented code and turning it around into best-in-class code redesigning costly compute and data processes and aligning to best development standards
- Experienced in working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding.
- At least 3 years of experience designing software systems with intense computational needs across real time and batch process.
- Experience and understanding of Supervised, unsupervised machine learning techniques
- Exposure to data ingestion, ETL tools such as Talend, modeling tools,



Performance Management tooling such as Pepper data, Cloudera stack will be a plus
- Knowledge of data management, data governance, data security and regulatory practices
- Ability to identify, clearly articulate and solve complex business problems and present them to the management in a structured and simpler form
- Should have experience of working in onsite, offsite delivery model
- Experience working with large and multiple datasets, data warehouses and ability to pull data using relevant programs and coding.
- Previous related experience preferred
- High attention to detail

Education :

- Bachelors/University degree or equivalent experience

This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. Job Family Group :Decision Management

- Job Family : Data/Information Management
- Time Type : Full time
- Most Relevant Skills :Please see the requirements listed above.
- Other Relevant Skills :For complementary skills, please see above and/or contact the recruiter.

📌 Big Data Engineer - Python and Spark (Pune)
🏢 Citi
📍 Pune