• Data Engineer/Technology Leader - ETL/Machine Learning Jobs in Bangalore,India

  • The Modern Dimension
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  • 4 - 10 Years
  • Posted : above 1 month

Job Description:

Job Title Technology Leader

Experience - 4+ years

Job Band

Corresponding Designation Team Lead (Data Engineer)

Career Stream Technology

Reporting Position Director of Engineering

No of Direct Reportees 2

Total Span of Control Technology and Product

Location Bangalore

Number of Working Days 5

Shift Working Regular

Key Job Purpose To amplify the Data Science progress in the organisation

Roles span of influence Product, Technology

Key Tasks/Responsibilities

- Machine learning pipelines and ETL processes that operate at arbitrary scale

- Reliable, stateless services that can be dynamically scaled and continuously deployed

- Analytical jobs and services to measure model performance offline and in production

- Tooling to help us productionize machine learning models faster

- We expect you to own modules end to end and take complete ownership of the products you deliver

- Lead from the front, when it comes to delivering high quality work products Serve as a mentor to the team

- Ability to work in ambiguous environment without day-to-day guidance and direction Can handle the uncertainty of unsolved problems

- Create and define performance metrics Ideate, innovate and hack through the existing systems to improve performance

- Thorough understanding of the product specs and workflows Breakdown the requirements into smaller tasks and deliver via agile methodologies

- Perform code reviews, set coding practices and guidelines within the team

- Performance Metrics Model Deployment

- Data Scientist iteration velocity

- Team Management

Job Incumbent Requirements (Knowledge/Skill/Experience)

Education BE /B Tech from Tier I

Training Requirement

Functional Competencies (Mandatory)

- Functional programming in languages like Scala, Haskell, or F# Experience with functional programming on Spark is a plus

- Object oriented programming

- Data modeling and schema evolution tools

- Parallelism, concurrency, and distributed system concepts (knowledge of CQRS, Event Sourcing, CAP Theorem)

- Understand what turning the database inside out means and its relevance to distributed commit logs and stream processing frameworks

- Expert knowledge of SQL and data querying tools & libraries

- Microservice architecture design Prior experience with A/B testing machine learning services before deployment is a plus

- Machine learning fundamentals

- API design and evolution

- Big data frameworks like Spark, and Hadoop

- Modern distributed databases like MongoDB, Cassandra, and Riak

- Stream processing frameworks such as Kafka, Flink, Storm, and Samza

- AWS systems like EC2, SQS, EMR and Redshift

Functional Competencies (Desirable)

- Machine learning libraries like scikit-learn and Tensor Flow

- Schema evolution tools such as Thrift, Avro Infrastructural tools like Docker, Zookeeper, Mesos, and Marathon and the ability to deploy machine learning services reliably with these tools or Protocol Buffers

- Foundational Competency (Mandatory) Drive & Ownership, Empathy, building winning Teams, Decision Making

- Foundational Competency (Desirable)

Key relationships/customer touch points

Internal Data sciences, New Business, GB

Profile Summary:

Employment Type : Full Time
Salary : Not Mentioned
Deadline : 18th Feb 2020

Key Skills:

Company Profile:

Not Mentioned

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