At Deriv, we are looking for a detail-oriented Senior Data Engineer with the capability to define the data pipeline of our future data models. You will leverage technologies such as Google Cloud Platform, Airflow, Python, Docker, and PostgreSQL to help provide the company with dependable business intelligence solutions. As part of this role, you will develop, test, and maintain architectures for data processing and build Extract, Transform, and Load (ETL) pipelines. You will be a key contributor to making our data warehouse trustworthy by ensuring data accuracy.
We are the Business Intelligence team. We lead the organisation in cultivating a data-driven culture as our company moves toward the future. We collect meaningful data and analytics for us to deeply understand our consumers and build more valuable products and services. What we 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.
A minimum of 5 years of experience in the data engineering field
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
Expertise in peer reviewing pipeline codes and suggesting improvements when required
Experience in helping teams make informed business decisions with data
Strong communication and presentation skills
Fluency in spoken and written English
Whats Good To 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
Annual performance bonus
Housing and transportation allowance
Casual dress code
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