- Applying strong technical experience building highly reliable services on managing and orchestrating a multi-petabyte scale data lake. You will have to work in a fast-paced environment.
- You are responsible to take vague requirements and transform them into solid solutions. and will work on solving challenging problems, where creativity is as crucial as your ability to write code and test cases.
- You will join our International Operations Data Engineering team which is responsible for building our data lake components, maintaining our big data pipelines and services and work directly with the business stakeholders, project, and platform teams to enable growth and support our field and back-office users in International Operations & Commercial Strategy & Corporate Affairs (CSCA).
- You will help our stakeholder teams ingest data faster into our data lake and find ways to make our data pipelines more efficient, or even come up ideas to help instigate self-serve data engineering within the setup.
- You will be responsible to building micro-services, architecting, designing, and enabling self-serve capabilities at scale.
- Should have 5 years of experience in Data and Analytics and overseen end-to-end implementation of data pipelines on cloud-based data platforms.
- Experience in Snowflake and Knowledge in transforming data using Data Build Tool.
- Strong programming skills in Python, PySpark and some combination Java, Scala (preferred).
- Experience in AWS and API Integration/Integration in General with Knowledge of data warehousing concepts.
- You have project/Internship experience writing SQL, structuring data, and data storage practices.
- Project/Internship experience of working with Spark, Hive, Airflow and other streaming technologies to process incredible volumes of streaming data .
- Project/Internship experience working on Amazon Web Services (in particular, using EMR, Kinesis, RDS, S3, SQS, Lambda, Glue, Databricks, Redshift, Athena and the like).
- Support use of data engineering toolsets (e.g. Python (especially PySpark), SQL, Notebooks).
- You have been involved assembling large, complex unstructured data sets that meet functional / non-functional business requirements.
- You have ability to identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- You can build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, Spark, and AWS services.
- You have built processes supporting data transformation, data structures, metadata, dependency, and workload management.
- Communicate and collaborate with the key stakeholders including follow-up on data loads and transformations .
- Participate in (and in some cases drive) activities related to implementation and enhancements
- Contribution to maturation of production processes related to data lake and user tools .
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Data Engineer - bangalore, India - Novo Nordisk
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Description
Job Description:
As Data engineer, you will have the opportunity: -
Qualifications
You are an ideal candidate if you meet following requisites.