Proficiency in Python
1.5+ years experience building, maintaining, and supporting complex data flows with structural and unstructural data
Experience working with distributed applications
Ability to use SQL for data profiling and data validation
English level — Intermediate
Nice to have:
Hands-on experience working with HDFS / or HIVE / or SQOOP
Understanding of AWS ecosystem and services such as EMR and S3
Familiarity with Apache Kafka and Apache Airflow
Experience in Unix commands and scripting
Experience and understanding of Continuous Integration and Continuous Delivery (CI/CD)
Understanding in performance tuning in distributed computing environment (such as Hadoop cluster or EMR)
Build end-to-end data flows from sources to fully curated and enhanced data sets. This can include the effort to locate and analyze source data, create data flows to extract, profile, and store ingested data, define and build data cleansing and imputation, map to a common data model, transform to satisfy business rules and statistical computations, and validate data content
Modify, maintain, and support existing data pipelines to provide business continuity and fulfill product enhancement requests
Provide technical expertise to diagnose errors from production support teams
Vacation is 20 working days / till 20 working days per year for sick leaves
Full payment of taxes
Flexible work schedule
Opportunity for career growth
About the Customer:
The customer is an American company based in Chicago. It accelerates digital transformation for the insurance and automotive industries with AI, IoT and workflow solutions.
About the Project:
The customer has been working on an analytics platform since 2018. The platform is on Hadoop and the Hortonworks Data Platform, and the customer is planning on moving it to Amazon EMR in 2021. The customer has a variety of products, the data for all of which comes into one data lake on this analytics platform, which also allows the customer to do next generation analytics on the amassed data.
Hortonworks is the current vendor. It will be replaced by Amazon EMR. Tableau is going to be the BI vendor. Microstrategy currently exists and will be phased out by early 2023.
All data is sent to the data lake, and the customer can do industry reporting. These data are used by a data science team to build new products and an AI model.
We will be moving to real-time streaming using Kafka and S3. We are doing POC to use Dremio and Presto for the query engine.
We’re migrating to version 2.0 using Amazon EMR and S3, and Query engine is bucketed under 2.0 project.
Cross product analytics
Analytics for every new product customer has. Analytics team products is how the customer sells the products value to clients
Quarterly Business Review meetings use data to explain how customer’s product is helping clients in their business
You’ll get to work with a cross-functional team
You will learn the customer’s company business
Project Tech Stack:
Technologies used are all open source Hadoop, Hive, PySpark, Airflow, Kafka to name a few