About Us:
Consertus is a global capital program management and advisory firm that combines deep human expertise with advanced digital tools to deliver smarter, faster, and more sustainable outcomes. Headquartered in Miami, Florida, and supported by a team of more than 1,000 professionals worldwide, we help clients plan, execute, and optimize large-scale capital programs.
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
Qualifications/Requirements:
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
Additional Requirements / 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
Equal Employment Opportunity Statement:
Consertus is proud to be an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We welcome applicants from all backgrounds and identities, and we do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, veteran status, or any other protected status.