Data Engineer

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

About Quantiphi:

Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Quantiphi has seen 2.5x growth YoY since its inception in 2013, we don’t just innovate - we lead.

Headquartered in Boston, with 4,000+ professionals across the globe. Quantiphi leverages Applied AI technologies across multiple a. Industry Verticals (Telco, BFSI, HCLS etc.) and is an established Elite/Premier Partner of NVIDIA, Google Cloud, AWS, Snowflake, and others.

We’ve been recognized with:

• 17x Google Cloud Partner of the Year awards in the last 8 years.

• 3x AWS AI/ML award wins.

• 3x NVIDIA Partner of the Year titles.

• 2x Snowflake Partner of the Year awards.

• We have also garnered top analyst recognitions from Gartner, ISG, and Everest Group.

• We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators.

• We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023.

Be part of a trailblazing team that’s shaping the future of AI, ML, and cloud innovation.

Your next big opportunity starts here!

For more details, visit:Websiteor LinkedIn Page.

Role:Data Engineer

Experience Level:10+ years experience

Work Location:Canada (Remote)

Role Overview:

We are seeking an experienced Data Engineer who will contribute to best practice data engineering by designing and rigorously delivering production-grade streaming pipelines on a regular basis, while also encouraging and optimizing the daily execution of technical excellence across an empowered team. You will be responsible for enhancing and implementing batch and real-time data solutions already in progress, mentor other team members, and deliver both business and technical objectives through ambiguity and uncertainty.

Key Responsibilities:

• Lead and guide the design and implementation of scalable streaming data pipelines

• Engineer and optimize real-time data solutions using frameworks like Apache Kafka, Flink, Spark Streaming

• Collaborate cross-functionally with product, analytics, and AI teams to ensure data is a strategic asset

• Advance ongoing modernization efforts, deepening adoption of event-driven architectures and cloud-native technologies

• Drive adoption of best practices in data governance, observability, and performance tuning for streaming workloads

• Embed data quality in processing pipelines by defining schema contracts, implementing transformation tests and data assertions, enforcing backward-compatible schema evolution, and automating checks for freshness, completeness, and accuracy across batch and streaming paths before production deployment

• Establish robust observability for data pipelines by implementing metrics, logging, and distributed tracing for streaming jobs, defining SLAs and SLOs for latency and throughput, and integrating alerting and dashboards to enable proactive monitoring and rapid incident response

• Foster a culture of quality through peer reviews, providing constructive feedback and seeking input on your own work

Basic Qualifications:

• Principal Data Engineer with at least 10 years of professional experience in software or data engineering, including a minimum of 4 years focused on streaming and real-time data systems

• Proven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on contributor

• Deep expertise in streaming and real-time data technologies, including frameworks such as Apache Kafka, Flink, and Spark Streaming

• Strong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency pipelines

• Practical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data workloads

• Fluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expectations)

• Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using modern tools

• Solid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming environments

• Experience with Lakehouse architectures and related technologies, including Databricks, Azure ADLS Gen2, and Apache Hudi

Other Qualifications (OQs):

• Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and across the organization

• Strong analytical and problem-solving mindset

• Ability to learn quickly and adapt to new technologies, even when uncomfortable

• Self-starter who thrives with minimal supervision and collaborates effectively as a team player

• Excellent organizational and critical-thinking skills

• Comfortable leveraging AI tools to accelerate development

What’s in it for YOU at Quantiphi:

• Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.

• Upskill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.

• Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.

• Stay ahead of the curve—immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.