Position Description Summary

Position Details:

• Job Title : Data Engineer/Solution Architect
• Assistant Director

As a Data Engineer / Solutions Architect, you will collaborate with business, reporting, and other teams to understand business requirements and perform data analysis. You will also apply specialized knowledge to support the organization’s vision and direction, serving as your team's subject matter expert. Additionally, you will thrive on solving complex problems, enjoy fine-tuning performance, and be passionate about turning data into insights. This role is ideal for someone who’s equally comfortable designing solutions, building pipelines, debugging performance issues, and developing impactful Power BI dashboards. You’ll play a key role in architecting scalable data solutions, integrating disparate data sources, and delivering high-quality analytics that drive business decisions. Experience with DevOps practices and automation using Python will be key in streamlining the deployment and monitoring of data solutions.

Role & Responsibilities

• Design and develop scalable data pipelines using Azure Data Factory (ADF) and SQL-based transformations.

• Architect and implement data solutions that meet business needs and performance goals
  Build, enhance, and maintain Power BI reports and dashboards with a focus on usability and performance.

• Diagnose, debug, and optimize slow-running data processes and analytics queries
  Collaborate with stakeholders across engineering, analytics, and business functions to understand requirements and translate them into scalable technical solutions.

• Ensure data quality, integrity, and governance throughout the pipeline
  Implement DevOps best practices to automate testing, deployment, and monitoring of data pipelines and BI assets.

• Use Python for scripting, automation, and integration of cloud data workflows.

• Create technical documentation, data models, and architecture diagrams
  Stay up to date with advancements in cloud data technologies and recommend improvements

Requirements

• A bachelor’s degree in computer science, Software Engineering, or a related field is required.

• The candidate should have over 7 years of experience in Data Engineering and BI Solution development.

• They must possess strong expertise in Azure Data Factory, including linked services, datasets, pipelines, and triggers.

• Expert-level SQL skills are essential, including complex query design, optimization, and troubleshooting.

• Proficiency in Power BI is necessary, particularly in data modelling, DAX, report design, and performance tuning.

• A solid understanding of data warehousing concepts, ELT/ETL strategies, and data architecture best practices is crucial.

• The candidate should have experience in debugging data flows, diagnosing bottlenecks, and improving end-to-end performance.

• Proficiency in Python for scripting and automation is required.

• Experience with DevOps tools and CI/CD workflows (e.g., Git, Azure DevOps, GitHub Actions) is important.

• A passion for clean code, performance optimization, and designing robust, supportable systems is essential.

• Proficiency in AI-assisted development practices as part of the solution development toolkit is also required.

• The candidate should have experience in leading small teams and possess good people management skills.

• Excellent presentation and documentation skills, good business acumen, and sound knowledge of Agile principles and SDLC are also necessary.

Good to have

• Microsoft Certifications relevant to the role.

• Experience with Azure Synapse, Azure SQL DB, or Databricks.

• Knowledge of PowerShell or other automation tools a plus.

• Ability to balance speed with precision in a fast-paced environment.

• Understanding of integration technologies, APIs, and protocols

• Experience developing/managing chatbot using virtual agent will be an asset

We Value

• Curiosity-driven problem solvers.

• Proactive collaborators who bring solutions, not just issues.

• Engineers who care about both the technical design and the user outcome.

• Professionals who enjoy optimizing things that already “work” to make them better.