NTT DATA

Data Engineer (Production Support) for AWS EMR-远程居家办公

NTT DATA  •  Onsite  •  4 months ago
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Job Description

Data Engineer (Production Support) for AWS EMR with Spark, Scala and Talend or any ETL tool Experience

We are seeking a highly skilled and motivated Data Engineer specializing in Production Support for AWS EMR (Elastic MapReduce ) with spark, scala, Talend or any ETL tool knowledge to join our dynamic team. The ideal candidate will ensure the smooth operation, performance, and stability of large-scale distributed data processing pipelines and applications deployed on AWS EMR. This role requires a mix of strong technical expertise, problem-solving skills, and operational excellence.

Key Responsibilities

1. Production Support

  • Monitor, troubleshoot, and resolve issues in real-time for AWS EMR clusters and associated data pipelines.
  • Investigate and debug data processing failures, latency issues, and performance bottlenecks.
  • Provide support for mission-critical production systems as part of an on-call rotation.
  • Analytical and problem-solving skills applied to Big Data domain. Strong exposure in Object Oriented concepts and implementation.

2. Cluster Management

  • Manage AWS EMR cluster lifecycle, including creation, scaling, termination, and optimization.
  • Ensure effective resource utilization and cost optimization of clusters.
  • Apply patches and upgrades to EMR clusters and software components as needed.

3. Data Pipeline Maintenance

  • Maintain and support ETL/ELT pipelines built on tools such as Apache Spark, Hive, or Presto running on EMR.
  • Ensure data quality, consistency, and availability across pipelines and storage systems like S3, Redshift, Mysql or Snowflake.
  • Implement and monitor automated workflows using AWS tools like Step Functions, Lambda, and CloudWatch.

4. Performance Optimization

  • Analyze and optimize EMR job performance by tuning Spark/Hive configurations and improving query efficiency.
  • Identify and address inefficiencies in data storage and access patterns.
  • Providing optimal solutions for performance enhancement and fine tuning of current applications.

5. Monitoring and Reporting

  • Set up and manage monitoring tools (e.g., AWS CloudWatch, Datadog, or Prometheus) to track system health and performance.
  • Develop alerting mechanisms and dashboards for proactive issue identification.
  • Provide daily/weekly monitoring reports on job status and alert on any long running/resource consuming issues

6. Collaboration and Documentation

  • Collaborate with software developers, data scientists, and DevOps teams to resolve issues and optimize workflows.
  • Maintain comprehensive documentation for troubleshooting guides, operational workflows, and best practices.

Required Skills and Qualifications

Technical Expertise:

  • Proficiency in managing AWS services, particularly EMR, S3, Lambda, Step Functions, and CloudWatch.
  • Hands-on experience with distributed data processing frameworks like Apache Spark, Hive, or Presto.
  • Experience on Kafka, NiFi, Amazon Web Service (AWS), Maven, Ambari-TEZ, Stash and Bamboo.
  • Familiarity with data loading tools like Talend, Sqoop. Familiarity with cloud database like AWS Redshift, Aurora MySQL and PostgreSQL
  • Knowledge of workflow/schedulers like Oozie or Apache AirFlow.
  • Strong knowledge of Shell Scripting, python or Java for scripting and automation.
  • Familiarity with SQL and query optimization techniques.

Operational Skills:

  • Experience in production support for large-scale distributed systems or data platforms.
  • Ability to analyze logs, diagnose issues, and implement fixes in high-pressure scenarios.
  • Implement data modelling concepts, methodologies to optimize data warehouse solutions.
  • Manage detailed Standard Operating Procedure (SOP) using flow diagrams, source to target mapping, system architecture diagram and use cases

Problem-Solving:

  • Strong analytical skills to debug complex systems and resolve performance bottlenecks.
  • Soft Skills:
  • Effective communication skills to coordinate with cross-functional teams.
  • A proactive and customer-focused attitude to provide excellent production support.

Preferred Skills

  • Experience with CI/CD tools like Jenkins or GitLab for pipeline deployments.
  • Familiarity with container orchestration tools (e.g., Kubernetes, Docker).
  • Knowledge of data governance, security, and compliance in cloud environments.
  • Certifications in AWS (e.g., AWS Certified Big Data Specialty or AWS Certified Solutions Architect).

Education and Experience

  • Bachelor’s degree in computer science, Engineering, or a related field.
  • 10+ years of experience with atleast 3-5 years on AWS Cloud platform experience in data engineering, production support, or a similar role.

Data Engineer (Production Support) for AWS EMR with Spark, Scala and Talend or any ETL tool Experience

We are seeking a highly skilled and motivated Data Engineer specializing in Production Support for AWS EMR (Elastic MapReduce ) with spark, scala, Talend or any ETL tool knowledge to join our dynamic team. The ideal candidate will ensure the smooth operation, performance, and stability of large-scale distributed data processing pipelines and applications deployed on AWS EMR. This role requires a mix of strong technical expertise, problem-solving skills, and operational excellence.

Key Responsibilities

1. Production Support

  • Monitor, troubleshoot, and resolve issues in real-time for AWS EMR clusters and associated data pipelines.
  • Investigate and debug data processing failures, latency issues, and performance bottlenecks.
  • Provide support for mission-critical production systems as part of an on-call rotation.
  • Analytical and problem-solving skills applied to Big Data domain. Strong exposure in Object Oriented concepts and implementation.

2. Cluster Management

  • Manage AWS EMR cluster lifecycle, including creation, scaling, termination, and optimization.
  • Ensure effective resource utilization and cost optimization of clusters.
  • Apply patches and upgrades to EMR clusters and software components as needed.

3. Data Pipeline Maintenance

  • Maintain and support ETL/ELT pipelines built on tools such as Apache Spark, Hive, or Presto running on EMR.
  • Ensure data quality, consistency, and availability across pipelines and storage systems like S3, Redshift, Mysql or Snowflake.
  • Implement and monitor automated workflows using AWS tools like Step Functions, Lambda, and CloudWatch.

4. Performance Optimization

  • Analyze and optimize EMR job performance by tuning Spark/Hive configurations and improving query efficiency.
  • Identify and address inefficiencies in data storage and access patterns.
  • Providing optimal solutions for performance enhancement and fine tuning of current applications.

5. Monitoring and Reporting

  • Set up and manage monitoring tools (e.g., AWS CloudWatch, Datadog, or Prometheus) to track system health and performance.
  • Develop alerting mechanisms and dashboards for proactive issue identification.
  • Provide daily/weekly monitoring reports on job status and alert on any long running/resource consuming issues

6. Collaboration and Documentation

  • Collaborate with software developers, data scientists, and DevOps teams to resolve issues and optimize workflows.
  • Maintain comprehensive documentation for troubleshooting guides, operational workflows, and best practices.

Required Skills and Qualifications

Technical Expertise:

  • Proficiency in managing AWS services, particularly EMR, S3, Lambda, Step Functions, and CloudWatch.
  • Hands-on experience with distributed data processing frameworks like Apache Spark, Hive, or Presto.
  • Experience on Kafka, NiFi, Amazon Web Service (AWS), Maven, Ambari-TEZ, Stash and Bamboo.
  • Familiarity with data loading tools like Talend, Sqoop. Familiarity with cloud database like AWS Redshift, Aurora MySQL and PostgreSQL
  • Knowledge of workflow/schedulers like Oozie or Apache AirFlow.
  • Strong knowledge of Shell Scripting, python or Java for scripting and automation.
  • Familiarity with SQL and query optimization techniques.

Operational Skills:

  • Experience in production support for large-scale distributed systems or data platforms.
  • Ability to analyze logs, diagnose issues, and implement fixes in high-pressure scenarios.
  • Implement data modelling concepts, methodologies to optimize data warehouse solutions.
  • Manage detailed Standard Operating Procedure (SOP) using flow diagrams, source to target mapping, system architecture diagram and use cases

Problem-Solving:

  • Strong analytical skills to debug complex systems and resolve performance bottlenecks.
  • Soft Skills:
  • Effective communication skills to coordinate with cross-functional teams.
  • A proactive and customer-focused attitude to provide excellent production support.

Preferred Skills

  • Experience with CI/CD tools like Jenkins or GitLab for pipeline deployments.
  • Familiarity with container orchestration tools (e.g., Kubernetes, Docker).
  • Knowledge of data governance, security, and compliance in cloud environments.
  • Certifications in AWS (e.g., AWS Certified Big Data Specialty or AWS Certified Solutions Architect).

Education and Experience

  • Bachelor’s degree in computer science, Engineering, or a related field.
  • 10+ years of experience with atleast 3-5 years on AWS Cloud platform experience in data engineering, production support, or a similar role.

Data Engineer (Production Support) for AWS EMR with Spark, Scala and Talend or any ETL tool Experience

We are seeking a highly skilled and motivated Data Engineer specializing in Production Support for AWS EMR (Elastic MapReduce ) with spark, scala, Talend or any ETL tool knowledge to join our dynamic team. The ideal candidate will ensure the smooth operation, performance, and stability of large-scale distributed data processing pipelines and applications deployed on AWS EMR. This role requires a mix of strong technical expertise, problem-solving skills, and operational excellence.

Key Responsibilities

1. Production Support

  • Monitor, troubleshoot, and resolve issues in real-time for AWS EMR clusters and associated data pipelines.
  • Investigate and debug data processing failures, latency issues, and performance bottlenecks.
  • Provide support for mission-critical production systems as part of an on-call rotation.
  • Analytical and problem-solving skills applied to Big Data domain. Strong exposure in Object Oriented concepts and implementation.

2. Cluster Management

  • Manage AWS EMR cluster lifecycle, including creation, scaling, termination, and optimization.
  • Ensure effective resource utilization and cost optimization of clusters.
  • Apply patches and upgrades to EMR clusters and software components as needed.

3. Data Pipeline Maintenance

  • Maintain and support ETL/ELT pipelines built on tools such as Apache Spark, Hive, or Presto running on EMR.
  • Ensure data quality, consistency, and availability across pipelines and storage systems like S3, Redshift, Mysql or Snowflake.
  • Implement and monitor automated workflows using AWS tools like Step Functions, Lambda, and CloudWatch.

4. Performance Optimization

  • Analyze and optimize EMR job performance by tuning Spark/Hive configurations and improving query efficiency.
  • Identify and address inefficiencies in data storage and access patterns.
  • Providing optimal solutions for performance enhancement and fine tuning of current applications.

5. Monitoring and Reporting

  • Set up and manage monitoring tools (e.g., AWS CloudWatch, Datadog, or Prometheus) to track system health and performance.
  • Develop alerting mechanisms and dashboards for proactive issue identification.
  • Provide daily/weekly monitoring reports on job status and alert on any long running/resource consuming issues

6. Collaboration and Documentation

  • Collaborate with software developers, data scientists, and DevOps teams to resolve issues and optimize workflows.
  • Maintain comprehensive documentation for troubleshooting guides, operational workflows, and best practices.

Required Skills and Qualifications

Technical Expertise:

  • Proficiency in managing AWS services, particularly EMR, S3, Lambda, Step Functions, and CloudWatch.
  • Hands-on experience with distributed data processing frameworks like Apache Spark, Hive, or Presto.
  • Experience on Kafka, NiFi, Amazon Web Service (AWS), Maven, Ambari-TEZ, Stash and Bamboo.
  • Familiarity with data loading tools like Talend, Sqoop. Familiarity with cloud database like AWS Redshift, Aurora MySQL and PostgreSQL
  • Knowledge of workflow/schedulers like Oozie or Apache AirFlow.
  • Strong knowledge of Shell Scripting, python or Java for scripting and automation.
  • Familiarity with SQL and query optimization techniques.

Operational Skills:

  • Experience in production support for large-scale distributed systems or data platforms.
  • Ability to analyze logs, diagnose issues, and implement fixes in high-pressure scenarios.
  • Implement data modelling concepts, methodologies to optimize data warehouse solutions.
  • Manage detailed Standard Operating Procedure (SOP) using flow diagrams, source to target mapping, system architecture diagram and use cases

Problem-Solving:

  • Strong analytical skills to debug complex systems and resolve performance bottlenecks.
  • Soft Skills:
  • Effective communication skills to coordinate with cross-functional teams.
  • A proactive and customer-focused attitude to provide excellent production support.

Preferred Skills

  • Experience with CI/CD tools like Jenkins or GitLab for pipeline deployments.
  • Familiarity with container orchestration tools (e.g., Kubernetes, Docker).
  • Knowledge of data governance, security, and compliance in cloud environments.
  • Certifications in AWS (e.g., AWS Certified Big Data Specialty or AWS Certified Solutions Architect).

Education and Experience

  • Bachelor’s degree in computer science, Engineering, or a related field.
  • 10+ years of experience with atleast 3-5 years on AWS Cloud platform experience in data engineering, production support, or a similar role.
NTT DATA

About NTT DATA

NTT DATA – a part of NTT Group – IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, digital & IT modernization and managed services. NTT DATA enables them, as well as society, to move confidently into the digital future. We are committed to our clients’ long-term success and combine global reach with local client attention to serve them in over 50 countries around the globe.

Industry
IT & Software
Company Size
10,000+ employees
Headquarters
Tokyo, JP
Year Founded
Unknown
Website
nttdata.com
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