Data Engineer
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Key skills for this role
About the Role
Design and maintain scalable data solutions, develop ETL processes, optimize SQL queries, and ensure data quality in a client-facing environment.
Key Skills for This Role
Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and load data from multiple sources
- Develop and optimize complex SQL queries, stored procedures, and database objects for high performance data processing
- Design and implement data models, including relational, dimensional (star/snowflake), and analytical schemas
- Lead the design and evolution of data warehouse architectures, including staging layers, data marts, and enterprise data models
- Build and maintain data integration solutions using APIs, flat files, and other data exchange mechanisms
- Develop backend data processing and automation solutions using Python
- Ensure data quality, integrity, and consistency through validation, monitoring, and testing processes
- Collaborate with stakeholders to gather requirements and translate them into scalable technical solutions
- Optimize and troubleshoot data systems and pipelines to ensure performance, reliability, and scalability
- Demonstrate ownership of deliverables, ensuring quality, timeliness, and alignment with client expectations
- Produce clear technical documentation including data mappings, data models, and pipeline designs
- Provide guidance on data engineering best practices, including data modelling, pipeline design, and performance optimization
Requirements
- Strong technical expertise in data engineering
- Experience designing scalable data solutions in a fast paced, client facing environment
- Ability to work independently
Full Job Posting
Overview
- As a Data Engineer, you will play a key role in designing, building, and maintaining scalable data solutions that support analytics, reporting, and integration across client engagements.
- You will work as part of a consulting team to develop robust data pipelines, data models, and backend systems that transform raw data into reliable, high quality datasets for business use.
- You will collaborate with cross functional teams and client stakeholders to design data architectures, implement ETL processes, and support modern data platforms.
- This role requires strong technical expertise, the ability to work independently, and experience designing scalable data solutions in a fast paced, client facing environment.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and ETL processes to ingest, transform, and load data from multiple sources
- Develop and optimize complex SQL queries, stored procedures, and database objects for high performance data processing
- Design and implement data models, including relational, dimensional (star/snowflake), and analytical schemas
- Lead the design and evolution of data warehouse architectures, including staging layers, data marts, and enterprise data models
- Build and maintain data integration solutions using APIs, flat files, and other data exchange mechanisms
- Develop backend data processing and automation solutions using Python
- Ensure data quality, integrity, and consistency through validation, monitoring, and testing processes
- Collaborate with stakeholders to gather requirements and translate them into scalable technical solutions
- Optimize and troubleshoot data systems and pipelines to ensure performance, reliability, and scalability
- Demonstrate ownership of deliverables, ensuring quality, timeliness, and alignment with client expectations
- Produce clear technical documentation including data mappings, data models, and pipeline designs
- Provide guidance on data engineering best practices, including data modelling, pipeline design, and performance optimization
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