Data engineer career at Danone Indonesia are responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise. Mainly tasked with transforming data into a format that can be easily analyzed, developing, maintaining, and testing infrastructures for data generation, and work closely with data scientists Danone Indonesia.
Danone Indonesia has grown their IT infrastructure, sales & marketing, and currently seeking professional to join the company to fill the position as Data Engineer.
Data Engineer Career Requirements
Create and maintain optimal data pipeline architecture and actively participate in design and data model reviews providing constructive feedback to platform owners
Ensure changes to the data environment are compliant to the architectural standards and collaborate with data governance owners to uncover and define business requirements
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and Azure or AWS ‘big data’ technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centers
Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems
Data Engineer Career Qualitications
Computer Science, Statistics, Informatics, Information Systems or another quantitative field
5+ years of experience in a Data Engineer role
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency, and workload management.
A successful history of manipulating, processing, and extracting value from large disconnected datasets.
Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.
Strong Agile project management and organizational skills
Experience with big data tools: Hadoop v2, Spark, Kafka, Hive, HBase, etc.
Experience with relational SQL and NoSQL databases, including Postgres and MongoDB.
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience with both On-Premise Microsoft SQL Server and Azure SQL and Data Services platforms
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
Experience reading and building data models
Proficient working in a fully Agile (SCRUM) environment
Excellent communication and facilitation skills
Team-oriented collaboration skills
Experience with Power BI preferred
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