Data Engineering Consultant

SDG Group

7d•Hybrid

About The Position

As a Data Engineer, you will play an important role in designing, developing, and delivering modern data solutions for SDG Group’s clients. Working as part of a consulting delivery team, you will partner with both technical and business stakeholders to understand data requirements and build reliable, scalable solutions that support analytics, reporting, AI, and broader data-driven initiatives. This role is well suited for someone with a strong foundation in data engineering who enjoys solving complex problems, working directly with clients, and continuing to expand their technical expertise across modern cloud and data platforms.

Requirements

Approximately 3–5+ years of experience in data engineering, data warehousing, data integration, analytics engineering, or a related technical discipline.
Experience within consulting or another client-facing environment is a plus.
Strong understanding of data pipelines, ETL/ELT processes, data integration, data warehousing, and data transformation concepts.
Strong SQL skills and working proficiency in Python or another relevant programming or scripting language.
Experience working with at least one modern cloud or data platform, such as AWS, Azure, GCP, Snowflake, Databricks, or comparable technologies.
Exposure to modern data engineering, orchestration, or transformation tools such as dbt, Matillion, Fivetran, Airflow, Informatica, Azure Data Factory, or similar technologies.
Understanding of dimensional modeling and modern data modeling concepts used within analytical environments.
Strong analytical skills with the ability to troubleshoot data issues, understand complex requirements, and translate business needs into technical solutions.
Strong written and verbal communication skills with the ability to collaborate effectively with clients, technical teams, and business stakeholders.
A proactive, collaborative approach and willingness to continuously learn new tools, technologies, and methodologies.

Nice To Haves

Experience within consulting or another client-facing environment is a plus.

Responsibilities

Design, build, test, and maintain scalable data pipelines and data processing solutions that support client analytics and business requirements.
Integrate data from a variety of structured and unstructured sources using modern ETL/ELT methodologies and data integration tools.
Develop and maintain data models and warehouse structures that support reporting, analytics, and downstream applications.
Contribute to the implementation of cloud-based data platforms using technologies across environments such as AWS, Azure, GCP, Snowflake, Databricks, or similar platforms.
Write efficient SQL and code to transform, validate, and manage data while following development, testing, documentation, and deployment best practices.
Work directly with clients and internal stakeholders to gather requirements, understand business challenges, communicate technical concepts, and deliver solutions aligned with client needs.
Identify opportunities to improve data quality, reliability, scalability, and performance across client data environments.
Work closely with data engineers, analysts, architects, data scientists, and business stakeholders throughout the project lifecycle.
Stay current with evolving data engineering technologies, methodologies, and industry best practices while contributing knowledge and ideas to the broader SDG community.