Job Description

The Challenge

As a Data Engineer in the Data Infrastructure team, you will build platforms and tools that churn through, process & analyze terabytes of data. You will have to build and manage the entire data flow pipeline. You will work on technologies such as  Apache Spark, Elasticsearch, Bigquery to build a scalable infrastructure that delivers recommendations to our users in real-time.

The pace of our growth is incredible – if you want to tackle hard and interesting problems at scale, and create an impact within an entrepreneurial environment, join us!

Roles and Responsibilities

  • You will work closely with Software Engineers & ML engineers to build a data infrastructure that fuels the needs of multiple teams, systems and products.

  • You will automate manual processes, optimize data delivery and build the infrastructure required for optimal extraction, transformation and loading of data required for a wide variety of use-cases using Apache Spark.

  • You will build stream processing pipelines and tools to support a vast variety of analytics and audit use-cases.

  • You will continuously evaluate relevant technologies, influence and drive architecture and design discussions.

  • You will work in a cross-functional team and collaborate with peers during the entire SDLC.



  • Minimum 4 years of work experience building data warehouse and BI systems.

  • Experience in either Go or Python (plus to have).

  • Experience in Apache Spark, Hadoop, Redshift, Bigquery.

  • Strong understanding of database and storage fundamentals.

  • Experience with the AWS stack and Google Cloud.

  • Ability to create data-flow design and write complex SQL / Spark-based transformations.

  • Experience working on real-time streaming data pipelines using Spark Streaming or Storm.


More Details
Employment Type: Full Time
Location: [REMOTE]
Experience Required: Mid-Senior Level
Date Published: 23 Nov 2021
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