Overview
Job Description:The role:
As a senior engineer in the Data team you will build and run production-grade data and machine learning pipelines and products at scale in an agile setup. You will work closely with our data engineers, architects and product managers to create the technology that generates and transforms data into applications, insights and experiences for our users.
Responsibilities:
Design, productionize and own end-to-end solutions that solve our customer's problems.
Define, plan and execute on strategic projects.
Communicate and align with peers and cross functional stakeholders.
Drive for technical excellence and pick the right balance between quality and speed of delivery.
Consistently steer the target architecture by identifying areas of critical need based on future growth.
Ensure code quality and maintainability by tackling tech debt, conducting code reviews, initiating refactoring and improving build and test systems.
What we are looking for:
You have expertise in Python and Java/Scala programming languages.
You have experience designing and productionizing large-scale distributed systems built around big data.
You have experience with batch and streaming technologies: e.g Apache Flink, Apache Spark, Apache Beam, Google DataFlow.
You have expertise with distributed data stores (Cassandra, Google BigTable, Redis, ClickHouse, Elasticsearch) and messaging systems (Kafka, Google PubSub) at scale.
You have experience with Linux, Docker, and public cloud (GCP, AWS, Azure).
You have a strong focus on execution, delivery and customer impact and craft code that is understandable, simple and clean.
You are an excellent communicator who can explain complex problems in clear and concise language to both business and technical audiences.
Job Requirements:
Kafka (2 - 3 yrs) - required
Data Engineering (4 - 6 yrs) - required
SQL (4 - 6 yrs) - required
Apache Spark (2 - 3 yrs) - required
Big Data (2 - 3 yrs) - required
Scala (2 - 3 yrs) - optional
AWS/GCP (2 - 3 yrs) - required
Time zone requirements:
The job requires working hours between 9 AM- 5 PM (GMT Time)