We are looking for a passionate Data Engineer to join your team. Our Data Engineer role offers the chance to collaborate with clients and design secure, scalable, and budget-friendly solutions leveraging the power of on-premises Technologies and Cloud (Azure | AWS).
To be successful, you'll need a blend of Cloud knowledge, data engineering experience, and a knack for clear communication and creative problem-solving. You will be responsible for the following duties, but not limited to:
Design and implement scalable data pipelines using Cloud services such as Glue, Redshift, S3, Lambda, EMR, Athena, Microsoft Fabric & Databricks.
Develop and maintain ETL processes to transform and integrate data from various sources.
Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions.
Optimize and tune performance of data pipelines and queries.
Ensure data quality and integrity through robust testing and validation processes.
Implement data security and compliance best practices.
Monitor and troubleshoot data pipeline issues and ensure timely resolution.
Stay updated with the latest developments in Data Engineering technologies and best practices.
The successful candidate must have comprehensive experience in the above, and must also meet the following requirements:
Holds a Bachelor's degree from an accredited university.
Industry experience: A minimum of two years of hands-on experience is required. Prior experience in the financial services industry would be beneficial but not mandatory.
Strong foundation in data engineering: We value hands-on experience and proven skills in building and managing data solutions using on-premises technologies or Cloud. While a Bachelor's degree in Computer Science, Engineering, or a related field is a plus, your ability to demonstrate expertise matters most.
Experience with core Cloud Data Services: Familiarity with Glue, Redshift, S3, Lambda, EMR, Athena, Microsoft Fabric or Databricks.
Experience with Big Data technologies: Knowledge of big data technologies such as Apache Spark, Hadoop, or Kafka.
Database Management: Experience working with relational databases like AWS RDS, MS SQL, Azure SQL DB or Postgres.
Solid Data Engineering background: Knowledge and experience of data modelling, ETL processes, and data warehousing.
Infrastructure as code (IaC) proficiency: Experience with tools like AWS CloudFormation, Terraform or Azure ARM/Bicep for automating infrastructure provisioning and deployments is crucial.
DevOps fluency: We seek a candidate with experience in CI/CD tools to streamline software development and delivery.
Communication and collaboration: Excellent communication, problem-solving, and analytical skills are key. The ability to present complex technical concepts in a clear and concise way.
Cloud Certification (a plus): While not mandatory, possessing a relevant Cloud certification demonstrates your commitment to professional development and validates your understanding of Cloud services and best practices.
The Ideal Monocle Data Engineer:
Strong problem-solving and analytical skills.
Excellent communication and collaboration skills.
Attention to detail and a commitment to data accuracy.
Be eager to learn new approaches and technologies.
Works well under pressure to meet client objectives.
Is sociable and enjoys interacting with others, both at work and at social events.