Senior RPA Platform Engineer

inimum educational qualification: B

• achelor’s degrees in computer science / software engineering or relevant field M

inimum experience: 7

• + years of experience in dealing with Data Lakehouse, RPA, configuration, architecture, designing, L2 & L23 Support O

ther Skills & Competence: P

latform Implementation and Support: P

• roficient in implementing, configuring, and supporting platform technologies, including Data Lakehouse and RPA ecosystems. Skilled in providing L2/L3 support for various data & RPA platform components. P

latform Installation, Management and Administration: E

• xpertise in installing, configuring, and managing diverse technology platforms, with a focus on Data Lake & RPA platforms like Hadoop, Cloudera, UiPath. Experience in administering Data Warehouse solutions and ensuring their reliability. B

ig Data Technology Proficiency: S

• killed in supporting and troubleshooting Big Data technologies such as Hadoop, Cloudera, Spark, Impala, and Kafka. Ability to diagnose and resolve issues related to Big Data platforms effectively. E

TL Process Management: C

• ompetent in managing ETL processes and tools like CDC, Informatica, and SSIS to ensure efficient data integration and processing. O

perating Systems Administration: E

• xpertise in administering Linux RedHat and Windows Servers operating systems commonly used in Big Data environments, ensuring smooth operations. C

loud and Virtualization Expertise: P

• roficient in setting up and managing containerized servers, cloud services, and virtualization environments. Hands-on experience with cloud-based data platform management and support. D

ata Engineering Principles Understanding: F

• amiliarity with data engineering principles, data warehousing concepts, and ETL processes to optimize data workflows. P

rogramming and Scripting Familiarity: F

• amiliarity with scripting and programming languages such as Python for developing data pipelines and automating tasks. S

ource Control and CI/CD Practices: C

• ompetence in software development methodologies, source control management, and continuous integration/delivery practices. A

rchitecture Design and Scalability: R

eporting Capability: S

• kill in providing regular reports including daily task, project status, issues, and resolutions, fostering transparency and alignment with project goals. A

rchitecture Design and Scalability: E

• xperience in designing scalable and resilient architectures for Data Lake & RPA environments, ensuring robustness and efficiency in handling large-scale data operations. T

echnical Leadership and Mentorship: A

• bility to provide technical leadership and mentorship to junior team members, guiding them in best practices and fostering a culture of continuous learning and improvement. P

roject Management Expertise: P

• roficiency in project management methodologies to lead and execute projects effectively, ensuring successful delivery and alignment with business objectives. S

takeholder Management: S

• killed in stakeholder management and aligning technical strategies with business objectives, ensuring that technical decisions support overarching business goals.

inimum educational qualification: B

• achelor’s degrees in computer science / software engineering or relevant field M

inimum experience: 7

• + years of experience in dealing with Data Lakehouse, RPA, configuration, architecture, designing, L2 & L23 Support O

ther Skills & Competence: P

latform Implementation and Support: P

• roficient in implementing, configuring, and supporting platform technologies, including Data Lakehouse and RPA ecosystems. Skilled in providing L2/L3 support for various data & RPA platform components. P

latform Installation, Management and Administration: E

• xpertise in installing, configuring, and managing diverse technology platforms, with a focus on Data Lake & RPA platforms like Hadoop, Cloudera, UiPath. Experience in administering Data Warehouse solutions and ensuring their reliability. B

ig Data Technology Proficiency: S

• killed in supporting and troubleshooting Big Data technologies such as Hadoop, Cloudera, Spark, Impala, and Kafka. Ability to diagnose and resolve issues related to Big Data platforms effectively. E

TL Process Management: C

• ompetent in managing ETL processes and tools like CDC, Informatica, and SSIS to ensure efficient data integration and processing. O

perating Systems Administration: E

• xpertise in administering Linux RedHat and Windows Servers operating systems commonly used in Big Data environments, ensuring smooth operations. C

loud and Virtualization Expertise: P

• roficient in setting up and managing containerized servers, cloud services, and virtualization environments. Hands-on experience with cloud-based data platform management and support. D

ata Engineering Principles Understanding: F

• amiliarity with data engineering principles, data warehousing concepts, and ETL processes to optimize data workflows. P

rogramming and Scripting Familiarity: F

• amiliarity with scripting and programming languages such as Python for developing data pipelines and automating tasks. S

ource Control and CI/CD Practices: C

• ompetence in software development methodologies, source control management, and continuous integration/delivery practices. A

rchitecture Design and Scalability: R

eporting Capability: S

• kill in providing regular reports including daily task, project status, issues, and resolutions, fostering transparency and alignment with project goals. A

rchitecture Design and Scalability: E

• xperience in designing scalable and resilient architectures for Data Lake & RPA environments, ensuring robustness and efficiency in handling large-scale data operations. T

echnical Leadership and Mentorship: A

• bility to provide technical leadership and mentorship to junior team members, guiding them in best practices and fostering a culture of continuous learning and improvement. P

roject Management Expertise: P

• roficiency in project management methodologies to lead and execute projects effectively, ensuring successful delivery and alignment with business objectives. S

takeholder Management: S