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Senior Data Engineer

Senior Data Engineer

  • Location India - Maharashtra - Pune
  • Travel required Yes - up to 10%
  • Job category IT&S Group
  • Relocation available Yes - Domestic (In country) only
  • Job type Professionals
  • Job code 133114BR
  • Experience level Intermediate
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Job summary

Grade HResponsible for supporting the delivery of business analysis and consulting processes and procedures for the defined specialism using sound technical capabilities, building and maintaining effective working relationships, ensuring relevant standards are defined and maintained, and supporting delivery of process and system improvements. Specialisms: Business Analysis; Data Management and Data Science; Digital Innovation.

Role Synopsis:

Role is key in ensuring availability and reliability of quality data that bp’s enterprise organization can use to detect, anticipate and prevent issues, provide insights to improve our operations, and have timely access to data that will allow our platform engineers to build the necessary automation for operational efficiency, self-healing, etc.

Key responsibilities:

  • Bachelor's (or higher) degree, preferably in Computer Science, MIS/IT, Mathematics or a hard science.
  • Experience Range: 8 to 12 years
  • Design complex software components, services, and applications. You’ll write design documents and review them with your software engineering and architecture peers, incorporating and quickly iterating on the feedback.
  • Own the delivery of your projects to production. You’ll follow best practices including writing high quality code, developing unit, functional, and performance tests, and creating end-to-end deployment pipelines to production to maintain a fast velocity.
  • Design and development of industrial scale data pipelines on Azure and AWS data platforms and services, building data ingestion and publishing pipelines, development and provisioning of data nodes and telemetry for performance and utilisation analytics, and support the development and build the automation of system performance and metrics
  • Collaboration with enterprise platform teams to utilize existing data products, ingestion patterns, or automations to avoid bespoke development while contributing to the enhancement and creation of these shared assets when gaps are identified
  • Own the end-to-end technical data lifecycle and corresponding data technology stack for their data domain and to have a deep understanding of the bp technology stack.
  • Write, deploy and maintain software to build, integrate, manage, maintain, and quality-assure data, and responsible for deploying secure and well-tested software that meets privacy and compliance requirements; develops, maintains and improves CI / CD pipeline.

Desirable Criteria:
  • You’ll have expertise in at least one language (C/C++, Java, C#, Python) including object-oriented design. You should be proficient in data structures, algorithms, runtime complexity, API and database design, as well as unit and functional test methodologies.
  • Deep and hands-on experience designing, planning, implementing, maintaining and documenting reliable and scalable data infrastructure and data products in complex environments
  • Data Manipulation: debug and maintain the end-to-end data engineering lifecycle of the data products; design and implementation of the end-to-end data stack, including designing complex data systems, interoperability across cloud platforms; experience on various types of data (streaming, structured and un-structured) is a plus.
  • Software Engineering: hands-on experience with SQL and NoSQL database fundamentals, query structures and design best practices, including scalability, readability, and reliability; you are proficient in at least one object-oriented programming language, Python [specifically data manipulation packages - Pandas, seaborn, matplotlib], Apache Spark or Scala.
  • Scalability, Reliability, Maintenance: proven experience in building scalable and re-usable systems that are used by others; knowledge and experience in automating operations as much as possible and identifying and building for long-term productivity over short-term speed/gains and execute on those opportunities to improve products or services.
  • Data Domain Knowledge: proven understanding of data sources and data and analytics requirements and typical SLAs associated to data provisioning and consumption at enterprise scale, with interest and experience in analysis of data or other enterprise platform operations activities.
  • Cloud Engineering: Recent experience utilizing data analytics offerings and services from Azure and AWS

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