Data Engineer
Indexed description
Our integrated services span digital, advisory, and delivery, empowering organizations to navigate complexity, manage risk, and achieve strategic goals in sectors including aviation, transportation, transit, water, healthcare, energy, education, government, commercial, life sciences, and technology.
At Consertus, we celebrate individual strengths, foster strong relationships, and promote flexibility in how and where we work. Join us to grow your career, develop your skills, and make a lasting impact as we transform how the world is built.
Discover how Consertus is driving transformative change for our clients, our people, and the communities we serve at www.consertus.com
About This Role
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
- Contribute to reusable frameworks, standards, and continuous improvement initiatives
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field
- 5+ years of experience in data engineering, software development, or related roles
- Advanced expertise in SQL, including complex queries, joins, aggregations, stored procedures, and performance tuning
- Strong experience with database design and schema development
- Hands-on experience with data warehousing concepts, including staging, data marts, and dimensional modeling
- Proficiency in Python for data processing, scripting, and automation
- Exposure to data warehousing concepts, including staging, data marts, and dimensional modelling
- Experience working with large, complex datasets across multiple systems
- Strong understanding of data modeling techniques (relational and dimensional)
- Strong analytical and problem-solving skills
- Effective written and verbal communication skills
- Experience with ETL tools such as SSIS, Azure Data Factory, or similar
- Familiarity with cloud data platforms (Azure, AWS, or GCP)
- Experience working with APIs and handling semi-structured data (JSON, XML)
- Exposure to data orchestration tools (e.g., Airflow, Prefect)
- Experience with version control systems such as Git
- Familiarity with BI/reporting tools (e.g., Power BI, Tableau) is a plus
- Experience working with APIs (REST/SOAP) and handling JSON/XML data structures is a plus
- Exposure to data warehousing concepts, including staging, data marts, and dimensional modelling
- Ability to manage multiple priorities in a fast-paced consulting environment
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