Senior RPA Platform Engineer

M

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.

M

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