We are seeking a passionate and driven Data Engineer to join our team. This role offers the opportunity to work closely with clients to design and deliver secure, scalable, and cost-effective data solutions across both on-premises environments and leading cloud platforms, including Azure and AWS.

To succeed in this role, you will bring a strong foundation in data engineering, cloud technologies, and a talent for clear communication and innovative problem-solving.

Key Responsibilities

• Design, build, and maintain scalable data pipelines using cloud technologies such as AWS Glue, Redshift, S3, Lambda, EMR, Athena, Microsoft Fabric, and Databricks.
• Develop and manage ETL processes to integrate and transform data from multiple sources.
• Collaborate with data scientists, analysts, and business stakeholders to translate requirements into high-quality data solutions.
• Optimise and tune data pipelines and queries for performance and efficiency.
• Ensure data quality, accuracy, and integrity through rigorous testing and validation.
• Implement data security, governance, and compliance best practices.
• Monitor, troubleshoot, and resolve data pipeline issues in a timely manner.
• Stay up to date with emerging data engineering tools, technologies, and industry best practices.

Minimum Requirements

• Bachelor’s degree from an accredited university.
• At least 2 years of hands-on experience in data engineering (financial services experience is advantageous but not required).
• Proven experience building and managing data solutions in cloud and/or on-premises environments.

Technical Skills & Experience

• Cloud Data Services: Experience with AWS (Glue, Redshift, S3, Lambda, EMR, Athena) and/or Microsoft Fabric or Databricks.
• Big Data Technologies: Familiarity with tools such as Apache Spark, Hadoop, or Kafka.
• Programming & Scripting: Proficiency in Python, Pandas, and SQL.
• Database Management: Experience with relational databases such as AWS RDS, MS SQL, Azure SQL Database, or PostgreSQL.
• Data Engineering Fundamentals: Strong understanding of data modelling, ETL processes, and data warehousing.
• Infrastructure as Code (IaC): Experience with tools such as AWS CloudFormation, Terraform, or Azure ARM/Bicep.
• DevOps Practices: Exposure to CI/CD tools and modern software delivery practices.

Key Competencies

• Strong analytical thinking and problem-solving abilities.
• Excellent communication skills, with the ability to present complex technical concepts clearly.
• High attention to detail and commitment to data accuracy.
• Ability to work independently and collaboratively within a team.
• Adaptability and eagerness to learn new technologies and approaches.
• Ability to perform under pressure and meet client deadlines.

The Ideal Candidate

The ideal Monocle Data Engineer is curious, collaborative, and results-driven. You thrive in a fast-paced environment, enjoy engaging with both clients and colleagues, and take pride in delivering high-quality, reliable data solutions. You align with Monocle’s values and contribute positively to both the professional and social culture of the team.