16+ Apache Hadoop Jobs in India

Roles and Responsibilities:

• Design, develop, and maintain the end-to-end MLOps infrastructure from the ground up, leveraging open-source systems across the entire MLOps landscape.
• Creating pipelines for data ingestion, data transformation, building, testing, and deploying machine learning models, as well as monitoring and maintaining the performance of these models in production.
• Managing the MLOps stack, including version control systems, continuous integration and deployment tools, containerization, orchestration, and monitoring systems.
• Ensure that the MLOps stack is scalable, reliable, and secure.

Skills Required:

• 3-6 years of MLOps experience
• Preferably worked in the startup ecosystem

Primary Skills:

• Experience with E2E MLOps systems like ClearML, Kubeflow, MLFlow etc.
• Technical expertise in MLOps: Should have a deep understanding of the MLOps landscape and be able to leverage open-source systems to build scalable, reliable, and secure MLOps infrastructure.
• Programming skills: Proficient in at least one programming language, such as Python, and have experience with data science libraries, such as TensorFlow, PyTorch, or Scikit-learn.
• DevOps experience: Should have experience with DevOps tools and practices, such as Git, Docker, Kubernetes, and Jenkins.

Secondary Skills:

• Version Control Systems (VCS) tools like Git and Subversion
• Containerization technologies like Docker and Kubernetes
• Cloud Platforms like AWS, Azure, and Google Cloud Platform
• Data Preparation and Management tools like Apache Spark, Apache Hadoop, and SQL databases like PostgreSQL and MySQL
• Machine Learning Frameworks like TensorFlow, PyTorch, and Scikit-learn
• Monitoring and Logging tools like Prometheus, Grafana, and Elasticsearch
• Continuous Integration and Continuous Deployment (CI/CD) tools like Jenkins, GitLab CI, and CircleCI
• Explain ability and Interpretability tools like LIME and SHAP

Have you streamed a program on Disney+, watched your favorite binge-worthy series on Peacock or cheered your favorite team on during the World Cup from one of the 20 top streaming platforms around the globe? If the answer is yes, you’ve already benefitted from Conviva technology, helping the world’s leading streaming publishers deliver exceptional streaming experiences and grow their businesses. 

Conviva is the only global streaming analytics platform for big data that collects, standardizes, and puts trillions of cross-screen, streaming data points in context, in real time. The Conviva platform provides comprehensive, continuous, census-level measurement through real-time, server side sessionization at unprecedented scale. If this sounds important, it is! We measure a global footprint of more than 500 million unique viewers in 180 countries watching 220 billion streams per year across 3 billion applications streaming on devices. With Conviva, customers get a unique level of actionability and scale from continuous streaming measurement insights and benchmarking across every stream, every screen, every second.

What you get to do in this role:

Work on extremely high scale RUST web services or backend systems.

Design and develop solutions for highly scalable web and backend systems.

Proactively identify and solve performance issues.

Maintain a high bar on code quality and unit testing.

What you bring to the role:

5+ years of hands-on software development experience.

At least 2+ years of RUST development experience.

Knowledge of cargo packages for kafka, redis etc.

Strong CS fundamentals, including system design, data structures and algorithms.

Expertise in backend and web services development.

Good analytical and troubleshooting skills.

What will help you stand out:

Experience working with large scale web services and applications.

Exposure to Golang, Scala or Java

Exposure to Big data systems like Kafka, Spark, Hadoop etc.

Underpinning the Conviva platform is a rich history of innovation. More than 60 patents represent award-winning technologies and standards, including first-of-its kind-innovations like time-state analytics and AI-automated data modeling, that surfaces actionable insights. By understanding real-world human experiences and having the ability to act within seconds of observation, our customers can solve business-critical issues and focus on growing their business ahead of the competition. Examples of the brands Conviva has helped fuel streaming growth for include: DAZN, Disney+, HBO, Hulu, NBCUniversal, Paramount+, Peacock, Sky, Sling TV, Univision and Warner Bros Discovery.  

Privately held, Conviva is headquartered in Silicon Valley, California with offices and people around the globe. For more information, visit us at www.conviva.com. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets! 

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
4. Work with Data, Analytics & Tech team to extract, arrange and analyze data
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
7. Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
8. Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
9. Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.

1. SQL
2. Ruby or Python(Ruby preferred)
3. Apache-Hadoop based analytics
4. Data warehousing
5. Data architecture
6. Schema design
7. ML

1.  Prior experience of 2 to 5 years as a Data Engineer.
2. Ability in managing and communicating data warehouse plans to internal teams.
3. Experience designing, building, and maintaining data processing systems.
4. Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
5. Excellent analytic skills associated with working on unstructured datasets.
6. Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.

• Responsibilities
       - Responsible for implementation and ongoing administration of Hadoop
  infrastructure.
       - Aligning with the systems engineering team to propose and deploy new
  hardware and software environments required for Hadoop and to expand existing
  environments.
       - Working with data delivery teams to setup new Hadoop users. This job includes
  setting up Linux users, setting up Kerberos principals and testing HDFS, Hive, Pig
  and MapReduce access for the new users.
       - Cluster maintenance as well as creation and removal of nodes using tools like
  Ganglia, Nagios, Cloudera Manager Enterprise, Dell Open Manage and other tools
       - Performance tuning of Hadoop clusters and Hadoop MapReduce routines
       - Screen Hadoop cluster job performances and capacity planning
       - Monitor Hadoop cluster connectivity and security
       - Manage and review Hadoop log files.
       - File system management and monitoring.
       - Diligently teaming with the infrastructure, network, database, application and
  business intelligence teams to guarantee high data quality and availability
       - Collaboration with application teams to install operating system and Hadoop
  updates, patches, version upgrades when required.
      
  READ MORE OF THE JOB DESCRIPTION 
  Qualifications
  Qualifications
       - Bachelors Degree in Information Technology, Computer Science or other
  relevant fields
       - General operational expertise such as good troubleshooting skills,
  understanding of systems capacity, bottlenecks, basics of memory, CPU, OS,
  storage, and networks.
       - Hadoop skills like HBase, Hive, Pig, Mahout
       - Ability to deploy Hadoop cluster, add and remove nodes, keep track of jobs,
  monitor critical parts of the cluster, configure name node high availability, schedule
  and configure it and take backups.
       - Good knowledge of Linux as Hadoop runs on Linux.
       - Familiarity with open source configuration management and deployment tools
  such as Puppet or Chef and Linux scripting.
       Nice to Have
       - Knowledge of Troubleshooting Core Java Applications is a plus.

Data Platform engineering at Uber is looking for a strong Technical Lead (Level 5a Engineer) who has built high quality platforms and services that can operate at scale. 5a Engineer at Uber exhibits following qualities: 

• Demonstrate tech expertise › Demonstrate technical skills to go very deep or broad in solving classes of problems or creating broadly leverageable solutions. 
• Execute large scale projects › Define, plan and execute complex and impactful projects. You communicate the vision to peers and stakeholders.
• Collaborate across teams › Domain resource to engineers outside your team and help them leverage the right solutions. Facilitate technical discussions and drive to a consensus.
• Coach engineers › Coach and mentor less experienced engineers and deeply invest in their learning and success. You give and solicit feedback, both positive and negative, to others you work with to help improve the entire team.
• Tech leadership › Lead the effort to define the best practices in your immediate team, and help the broader organization establish better technical or business processes.

What You’ll Do

• Build a scalable, reliable, operable and performant data analytics platform for Uber’s engineers, data scientists, products and operations teams.
• Work alongside the pioneers of big data systems such as Hive, Yarn, Spark, Presto, Kafka, Flink to build out a highly reliable, performant, easy to use software system for Uber’s planet scale of data. 
• Become proficient of multi-tenancy, resource isolation, abuse prevention, self-serve debuggability aspects of a high performant, large scale, service while building these capabilities for Uber's engineers and operation folks.

What You’ll Need

• 7+ years experience in building large scale products, data platforms, distributed systems in a high caliber environment.
• Architecture: Identify and solve major architectural problems by going deep in your field or broad across different teams. Extend, improve, or, when needed, build solutions to address architectural gaps or technical debt.
• Software Engineering/Programming: Create frameworks and abstractions that are reliable and reusable. advanced knowledge of at least one programming language, and are happy to learn more. Our core languages are Java, Python, Go, and Scala.
• Data Engineering: Expertise in one of the big data analytics technologies we currently use such as Apache Hadoop (HDFS and YARN), Apache Hive, Impala, Drill, Spark, Tez, Presto, Calcite, Parquet, Arrow etc. Under the hood experience with similar systems such as Vertica, Apache Impala, Drill, Google Borg, Google BigQuery, Amazon EMR, Amazon RedShift, Docker, Kubernetes, Mesos etc.
• Execution & Results: You tackle large technical projects/problems that are not clearly defined. You anticipate roadblocks and have strategies to de-risk timelines. You orchestrate work that spans multiple teams and keep your stakeholders informed.
• A team player: You believe that you can achieve more on a team that the whole is greater than the sum of its parts. You rely on others’ candid feedback for continuous improvement.
• Business acumen: You understand requirements beyond the written word. Whether you’re working on an API used by other developers, an internal tool consumed by our operation teams, or a feature used by millions of customers, your attention to details leads to a delightful user experience.