Position: Data Engineer
Company: AllSTARSIT
Category: Data Engineer
Experience required: 3y
English level: intermediate

You are passionate about data, and it’s appliances, from data
collection, data modeling, cleaning and storing to analysing & building ML models to enrich business capabilities. You welcome responsibility and take processes from one end to the other.
On top of all that, you know your way around when you need
to enhance the data pipeline, you’re not afraid of some ETLs and in fact you’ve built some pipelines in the past and can do magic with SQL.
That means for us that you are **our data guy** :)

We work in small, KPI-oriented teams while following Agile work methods. We use continuous integration and continuous delivery methodologies to run quickly and efficiently while maintaining a high level of user experience. We need you to help us grow our business and write clean and performant code for our highly scalable systems that support our dear customers.

**Specialization:** Online media, Advertising
**Headquarters:** New York
**Years on the market:** Since 2014

**Previous experience:**
- At least 3 years of experience as a data engineer
- Expertise in different types of databases and data warehouses, including SQL and NOSQL
- Work with large data sets and distributed computing tools (Hadoop, Pig, Spark, Beam etc)
- Experience with a reporting platform like Tableau/Looker/DataStudio
- Analyzing and processing tons and tons of data, and use it to give actionable insights 
- Being an independent, self-learner who understands business processes and can translate business needs into data model
- Upper-intermediate+ English.

**As a plus:**
- Experience with using google cloud data stack (dataflow, pubsub, bigquery, etc)
- Google-Pubsub or Kafka expertise
- Having run models in production

**Scope of work:**
- Being responsible for designing, implementing and maintaining data pipelines from different sources.   
- Owning the data development process end-to-end including business understanding, methodology, QA and maintenance.
- Working closely with the Head of data and VP of R&D to define goals and objectives.