Sr Data Engineer

About MIR Digital:

At MIR Digital, we're more than a company—we're a collective of innovators, builders, and change-makers. We believe in empowering our team members to shape their own success while contributing to meaningful projects that drive business transformation. With a growing network of skilled professionals, we're committed to delivering impactful digital solutions that empower our clients to excel in an ever-evolving world.

Founded with a mission to redefine the digital landscape, MIR Digital has become a trusted partner for organizations seeking cutting-edge IT and business solutions. Our team thrives on collaboration, expertise, and a shared vision for achieving exceptional results.

This is your opportunity to join a forward-thinking team and build your career with MIR Digital.

About the Role

We are seeking Senior Data Engineers to design, build, and optimize scalable data pipelines that drive our advertising ecosystem. In this role, you will ensure the accuracy, reliability, and performance of our data infrastructure to support effective campaign management and reporting. You will also have the opportunity to work on high-scale ad tech solutions while collaborating closely with cross-functional teams.

• Location: Hybrid – GTA

Key Responsibilities

As a Senior Data Engineer, you will design and develop scalable data pipelines and ETL/ELT processes to support the Retail Media Platform, while building and maintaining data models, semantic layers, and reporting structures that enable self-serve analytics. You will develop and optimize real-time streaming pipelines and dashboards for campaign reporting and analytics, collaborating with stakeholders across product, marketing, operations, and analytics to gather requirements and deliver robust data solutions. Your responsibilities will include implementing testing, validation, and monitoring strategies to ensure data accuracy, completeness, and reliability, as well as optimizing the performance of pipelines, queries, and workflows to handle large-scale, high-velocity datasets. In this role, you will work closely with product managers, designers, and developers to foster a data-first culture and support hypothesis-driven product development, while also providing ad hoc reporting and insights that enable data-driven decision-making. Additionally, you will stay current with industry trends and emerging technologies in data engineering, analytics, and ad tech to continuously enhance the organization's data capabilities

Required Skills & Qualifications

Tech Stack Snapshot:

Languages: Python, Scala, Java

Data & Orchestration: BigQuery, Bigtable, Druid, DataProc, DBT, Airflow

Cloud Platform: Google Cloud Platform (preferred), AWS, Azure

Workflow & Versioning: Git, CI/CD pipelines

Visualization & Reporting: Real-time dashboards and semantic layers

The ideal candidate will have 3+ years of experience as a Data Engineer or in a similar role, with strong programming skills in Python, Scala, or Java for data processing and pipeline development. They should have experience with cloud platforms—preferably GCP—and hands-on expertise with technologies like BigQuery, Bigtable, Druid, DataProc, DBT, and Airflow. Advanced SQL skills, the ability to design and implement data models and semantic layers, and familiarity with real-time data processing and streaming dashboards are essential. A solid understanding of Git workflows, data warehousing concepts, governance, and data quality best practices is also required.

Soft Skills & Collaboration

The ideal candidate will have strong communication skills with the ability to simplify complex data concepts for non-technical stakeholders, along with excellent stakeholder management capabilities to balance multiple priorities effectively. They should bring proven experience working in Agile/Scrum environments with cross-functional teams, thrive as a collaborative team player in fast-paced settings, and demonstrate a passion for continuous learning and staying current with evolving technologies.

Nice to Have

Prior experience in AdTech or retail media platforms is highly desirable, along with familiarity in real-time bidding, high-volume ad-serving systems, and event-driven architectures. Exposure to real-time analytics platforms and an understanding of machine learning pipelines or integrating ML-driven insights into reporting are also valuable.