Are you ready to revolutionise the way we build data?
At Deriv, we’re looking for a talented Data Engineer to spearhead our digital transformation initiatives. In this role, you’ll lead the organisation in cultivating a data-driven culture as our company moves toward the future.
As a key technology team member, you’ll be responsible collecting meaningful data and analytics to deeply understand our consumers and build more valuable products and services. What you do is incredibly important in driving smart marketing decisions, optimising our business, and increasing profitability.
Ensure data integrity while extracting data from in-house and third-party complex sources and manage its systematic storage. Responsible for data security, accuracy, and accessibility.
Provide tangible business solutions and decisions using your expertise in the data engineering domain.
Design and build high-performance, secure, and scalable company data warehouse and pipeline to support data science projects following best practices.
Debug and resolve complex issues, and recommend improvements to ensure a well-functioning ETL pipelined architecture.
Transform raw data into easy-to-use tables for the Data Analysts.
Keep up-to-date on company products and new releases to efficiently plan changes in our data warehouse or pipelines.
Have a good background in cybersecurity and data protection
Proficiency in using data pipeline and workflow management tools such as Luigi
Exposure to maintaining and monitoring database health and resolving errors
Experience in managing stakeholders’ expectations and technical requirement gathering
Familiarity with container technologies such as Docker
A fintech background
Have a minimum of 6 years of experience in the data engineering field
Have expertise in data modelling techniques such as Kimball star schema, Anchor modelling, and Data vault
Competence in object-oriented or object function scripting languages such as Python
Proficiency in relational SQL and NoSQL databases, preferably with PostgreSQL, PITR, Pg_basebackup, WAL archival, and Replication
Familiarity with column-oriented storage or data warehouses such as parquet, Redshift, and Bigquery
In-depth skills in developing and maintaining ETL/ELT data pipelines and workflow management tools such as Airflow
Hands-on experience with Google Cloud Platform (GCP) services such as BigQuery, scheduled queries, Cloud Storage and Cloud Functions
Familiar with alerting and self-recovery methods concerning data accuracy
Analytical skills with the ability to transform data into optimal business decisions