Minimum 5 years of development and design experience in experience as Data EngineerExperience on Big Data platforms and distributed computing (e.g. Hadoop Map/Reduce Spark HBase Hive) Experience in data pipeline software engineering and best practice in python (linting unit tests integration tests git flow/pull request process object-oriented development data validation algorithms and data structures technical troubleshooting and debugging bash scripting )Experience in Data Quality Assessment (profiling anomaly detection) and data documentation (schema dictionaries) Experience in data architecture data warehousing and modelling techniques (Relational ETL OLTP) and consider performance alternativesUsed SQL PL/SQL or T-SQL with RDBMSs production environments no-SQL databases nice to haveLinux OS configuration and use including shell scripting. Well versed with Agile DevOps and CI/CD principles (GitHub Jenkins etc.) and actively involved in solving troubleshooting issues in distributed services ecosystem Experience in Agile quality of technical and application architecture and design of systems across the research and benchmark technology against other best in class technologies. Experience in Banking Financial and Fintech experience in an enterprise environment preferred Able to influence multiple teams on technical considerations increasing their productivity and effectivenessby sharing deep knowledge and -motivator and self starter Ability to own and drive things without supervision and works collaboratively with the teams across the organization. Have excellent soft and interpersonal skills to interact and present the ideas to team. The engineer shouldve good listening skills and speaks clearly in front of team stakeholders and management. The engineer should always carry positive attitude towards work and establishes effective team relations and builds a climate of trust within the team. Should be enthusiastic and passionate and creates a motivating environment for the team.