Decision Inc. is seeking talented Data Engineers to join our Data, Information, and Analytics practice as client-facing consultants. You will design and build modern data platforms, lead delivery across diverse industries, and help our clients become genuinely data-driven businesses. You will work across the full engineering lifecycle, from architecture and pipeline development to mentoring junior colleagues and contributing to pre-sales engagements. A passion for data, a curiosity for new technologies, and the ability to adapt quickly to different business environments are essential. What You Will Do Design and build scalable data platforms using modern cloud‑native and Lakehouse architectures Develop and optimise data pipelines using Python, SQL, and tools such as Azure Data Factory, AWS Glue, Google Cloud Dataflow, Databricks, and dbt Modernise legacy data environments, migrating from on‑premises solutions to cloud‑native platforms such as Microsoft Fabric, Azure Synapse Analytics, AWS Redshift, Google BigQuery, or Databricks Engage with clients to conceptualise data solutions aligned to their business strategy Support our sales team with pre‑sales activities, proof‑of‑concept deliveries, and technical proposals Provide technical guidance and mentorship to junior and intermediate consultants Lead technical reviews and contribute to consultants' growth plans Identify opportunities to automate manual processes, optimise data delivery, and improve infrastructure scalability Work with stakeholders, including executive, product, and analytics teams, to address data infrastructure needs Drive knowledge sharing through technical blogs, internal forums, and workshops Balance billable project work with team support responsibilities What We Are Looking For 3–5 years of hands‑on experience in data engineering Strong proficiency in Python and/or SQL, including query optimisation and working with both relational and non‑relational databases Experience designing and building data pipelines, data models, and lakehouse architectures (medallion pattern) Practical experience with one or more cloud platforms: Microsoft Azure (Data Factory, ADLS Gen2, Synapse Analytics, Fabric), AWS (Glue, S3, Redshift, EMR), or GCP (Dataflow, BigQuery, Cloud Storage, Dataproc) Familiarity with Databricks, Snowflake, Delta Lake, and PySpark Understanding of data transformation frameworks such as dbt Experience with version control (Git) and CI/CD practices for data workflows Strong analytical skills and the ability to perform root cause analysis on complex data problems Good communication and stakeholder engagement skills Qualifications Bachelor's degree in computer science, Information Systems, Information Technology, or a related field A master's degree in a relevant field is advantageous Ideal Certifications DP‑700 – Microsoft Fabric Data Engineer Associate DP‑203 – Microsoft Azure Data Engineer Associate Databricks DE Associate – Databricks Certified Data Engineer Associate Google Professional Data Engineer (GCP) AWS Data Engineer – AWS Certified Data Engineer – Associate Databricks DE Professional – Databricks Certified Data Engineer Professional #J-18808-Ljbffr