Data Engineer

• As a Data Engineer, you will be
• responsible for designing, developing, and maintaining data infrastructure and
• analytics solutions to support data-driven decision-making and reporting. You will collaborate with other internal teams such as Business
• Intelligence, Data Operations, IT, and other stakeholders to understand
• business requirements and translate them into
• technical solutions. Your role will potentially involve working with large
• and complex data sets, implementing data pipelines, and ensuring data accuracy,
• integrity, and availability.

Responsibilities

• Develop and maintain data
• infrastructure: Design, build, and optimize data pipelines, ETL/ELT processes,
• and data warehouses to support efficient data collection, storage, and
• retrieval.
• Data modelling and schema
• design: Define data models and schemas to enable efficient data analysis,
• reporting, and visualization. Ensure adherence to data governance and data
• quality standards.
• Data transformation and
• manipulation: Cleanse, transform, and aggregate data to derive meaningful
• insights. Identify data inconsistencies, outliers, and anomalies and implement
• appropriate solutions.
• Implement data analytics
• solutions: Collaborate with different company departments to understand their
• requirements and develop analytics solutions that meet their needs.
• Documentation and
• communication: Document data processes, data flows, and data structures.
• Clearly communicate technical concepts and findings to non-technical
• stakeholders such as Credit/Structuring, Operations, Legal, etc.

Requirements

What are we looking for

• Bachelor's degree in Computer
• Science, Information Systems, Data Science/Analytics, or a related field.
• 6 years of experience as an Data
• Engineer, Analytical Engineer, Data Analyst, Business Intelligence Engineer, or
• similar role

Experience working with

• finance-related data sets (ex: FinTech, Lending, Financial Services, or related
• industries)
• Advanced SQL skills and
• experience working with complex data sets.
• Understanding of the following
• is advantageous:
• oData Modelling
• oData Governance
• oETL/ELT practices
• oData transformations with dbt
• oData warehousing with Snowflake
• oCloud computing with AWS
• oData orchestration tools (e.g. Airflow, Dagster)
• oAPI Usage and Integration
• Strong analytical and
• problem-solving skills, with the ability to transform complex data into
• actionable insights.
• Excellent communication and
• collaboration skills, with the ability to interact effectively with both
• technical and non-technical stakeholders.
• Strong attention to detail and
• a commitment to delivering high-quality work within deadlines.
• Willingness to stay updated
• with emerging technologies, tools, and best practices in data engineering and
• analytics. Ability to adapt to evolving business needs and work in a fast-paced
• environment.