logo
Description
About The Position:
As a Senior Data Engineer, you’ll join our data engineering team, working alongside AI engineers,
data scientists, backend engineers, analysts, and the BI team.
In this crucial role, you will take part in building our next-generation data platform that will advance
PwC as a data-driven company.
You’ll collaborate with different departments to identify data sources that shed light on every aspect
of our product, including user behavior, new feature adoption, operational, financial, marketing KPIs,
and more.
You will work with cutting-edge technologies and address the business needs of other department
members, based on an in-depth understanding of our business and landscape.
Responsibilities:
● End-to-end development of company data infrastructure
● Build and design high-performance, near real-time ETL/ELT processes incorporating current
and new data stack tools such as Airflow, AWS, GCP, Azure, Kubernetes, Databricks, dbt,
Spark, and Kafka.
● Build and design data platform components to enable clients to produce and consume data
● Develop, implement, and maintain change control, testing processes, and monitoring
infrastructure
● Build and design self-serve components that can speed up the development cycle and time
to market
● Research and implement best practices and new approaches to our current data stack and
systems
● Deliver software solutions through iterative and agile processes while maintaining software
quality and stability to current systems
Requirements
Requirements:
● 7+ years of experience in data engineering or backend engineering roles - a must
● Strong knowledge of backend programming languages (Python, Java, Go, Scala, or similar) -
a must
● Deep knowledge and strong experience deploying distributed data technologies and systems
(Spark, Kafka, Airflow, or similar) - a must
● Strong and proven knowledge working with data lakes, lakehouses, and data warehouses in
the cloud (Databricks, Snowflake, Trino, Cloud Storage, or similar)
● Advanced proficiency working with SQL / NoSQL databases
● Strong experience with ETL/ELT processes, data ingestion, data transformation, data
modeling, and monitoring.