Data Engineer, Regional
We are looking for Data Engineers who will help us define and build the next generation of data operations here in Kaodim.
The mission for the team will be to enable data democracy - enable continuous, controlled access and data-empowered decisions to every team in Kaodim to iterate and scale to datasets in the range of hundreds of GB (for now!). In this role you will also be working closely with special ops projects including targeted marketing, personalization, recommendations, automated/flexible pricing and our first iteration of machine learning.
We welcome candidates who are self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate should also be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.
What you will be doing
- Create and maintain optimal data pipeline architecture,
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- 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 Product, Data, Engineering and business teams to assist with data-related technical issues and support their data infrastructure needs.
- Maintain data security and integrity across geographical boundaries as the organization scales.
- 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.
What we'd like to see in the candidate
- 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 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.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- We are looking for a candidate with 3+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with common, open-source data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
- Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
- Experience with AWS data stack: EC2, EMR, RDS, Redshift, Athena, Firehose, Glue, or
- Experience with GCP data stack: data storage services, DataProc, DataFlow, BigQuery, PubSub
- Experience with at least two of object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- Experience and passion for Agile software processes, site reliability principles, rapid prototyping and responsible experimentation
- Experience in building machine learning platforms and pipelines for training and running machine learning models on distributed systems
Do you have what it takes?
Click Apply above or you can email your application to email@example.com