Senior Data Engineer Data Analyst,Python,SQL

About the Role/position

The ideal candidate is an experienced data pipeline builder and data wrangler, will act as technical data engineering expert in international team (multilocation). He/she will actively participate in optimizing data systems or building them from the ground up for our oversee customers.

Responsibilities:

The Data engineer will be responsible for:

• Develop and maintain data pipelines using ETL processes.
• Work closely with data science team to implement data analytics pipelines.
• Maintain security and data privacy, working closely with data protection officer.
• Implement scalable architectural models for data processing and storage.
• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time mode.
• Help in scoping, estimation, and planning for various projects in the enterprise.
• Provide technical support to project teams as needed.

Must have Technical Requirements / Qualifications

• B.S. in Computer Science, related fields or commensurate work experience.
• 5+ years of experience in software development with 3+ years of experience of relevant data engineering like Spark, PySpark, Hive, HDFS, Pig... and ETL with large amounts of data.
• Solid knowledge and experience of data processing languages, such as SQL, Python, and/or Scala.
• Hand on experience with real-time data stream platforms such as Kafka and Spark Streaming.
• Knowledge and experience on both relational databases (Oracle), NoSQL databases (e.g. MongoDB) and strong SQL querying skills, Performance Tuning are required.
• Experience on complex regulatory data integration projects.
• Agile based delivery knowledge
• Excellent English communication - verbal, written, and presentation skills.
• Strong teambuilding skills and teamwork orientation.
• Strong creative problem-solving skills.

Nice to have Technical Requirements / Qualifications

• DP-203 - Data Engineering on Microsoft Azure certificate.
• Knowledge of at least one cloud environment (Azure, GCP, AWS, IBM)
• Experience on Data Warehouse such as Teradata SQL, Informatica, Unix and Control-M.
• Experience of data visualisation tools (e.g Tableau, Quantexa and SAS).
• Experience on creating Slowly Changing Dimension type data tables in Hive using Spark framework

• Competitive salary, health insurance covered for employee and dependents
• Working on international projects. Professional and dynamic working environment
• Achieving valuable experience with variety projects, new technologies and hundreds of talents
• Receiving training opportunities including many technical seminars and soft skill training courses
• Good opportunity for promotion through regular performance review system
• Hybrid work