Position: Senior Data Engineer / Dealtale
Company: MWDN
Experience required: 5y
English level: upper

5+ years of experience as a Data Engineer
5+ years of experience with data warehousing technologies such as Amazon Redshift, Snowflake, Redis, MongoDB and experience with BI solutions development (DWH, ETL)
5+ years of experience in SQL and ETL tools like SSIS\ Informatica
5+ years of experience with Python
5+ years of experience in open-source Big Data tools like Hadoop, Hive, Spark, Presto, Sqoop
Experience with data platforms architecture, in particular, Big Data architecture , Deep understanding of big data storage formats, especially Apache Parquet, Snappy
Experience with AWS cloud services like S3 , EMR , Athena, Lambda, Kinesis, Glue, etc.
Experience with Docker and Kubernetes, Fargate, ECS and CI/CD based on Jenkins.
Experience with Cython, numpy, pandas, koalas, pyarrow, fastparquet, scipy, celery, async.io, django
Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
Willing to collaborate and problem solve in an open team environment.
Flexible and adaptable in regard to learning and understanding new technologies.
B.Sc. or higher degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field

WILL BE A PLUS
Experience with Linux administration
Experience with software architecture
Understanding of cloud security best practices.
Experience with agile development (Scrum, Kanban).
Experience supporting and working with cross-functional teams in a dynamic environment
Ability to take ownership and facilitate consensus among a diverse group of stakeholders.

Responsibilities
Create and maintain optimal data pipeline architecture
Assemble large, complex data sets that meet both functional & non-functional business requirements
Identify, design, and implement improvements in internal processes: Manual processes automation, data delivery optimizations, infrastructure re-designs for greater scalability, etc.
Use SQL and big data cloud technologies to build the infrastructure required for optimal loading, extraction, and transformation of data from a wide variety of sources
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 Fullstack team to assist with data-related technical issues and support their needs associated with data infrastructure
Work with data and analytics experts, striving to improve our data systems functionality


Dealtale helps marketing, sales & product teams optimize multi-touch customer journeys and boost performance & ROI by leveraging cutting-edge predictive modeling—fast. At Dealtale, we understand the frustrations and limitations that using multiple, complex digital tools create. So, we built a platform that integrates and prepares data for analysis and provides teams with a super-simple UI to get immediate answers—without worrying about coding, data silos, legacy data structures, data science, or engineering. Our mission is to empower non-analysts to focus on boosting revenue performance and delivering business value with deep insights. Get ready to work with everything connected to data: Expanding and optimizing our data pipeline architecture as well as data flows, building and improving our data systems.

Website: https://dealtale.com/about-dealtale