Data Engineer

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 wit

• h:17x Google Cloud Partner of the Year awards in the last 8 year
• s.3x AWS AI/ML award win
• s.3x NVIDIA Partner of the Year title
• s.2x Snowflake Partner of the Year award
• s.We have also garnered top analyst recognitions from Gartner, ISG, and Everest Grou
• p.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 accelerator
• s.We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 202

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Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovatio**

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For more details, vis
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**age.

Role: Data Eng**

ineerExperience L
evel: 10+ years exper

ienceWork Loca
tion: Canada (Re

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Role Ov**

erview: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 uncer

**tainty.

Key Responsib**

• ilities:Lead and guide the design and implementation of scalable streaming data p
• ipelinesEngineer and optimize real-time data solutions using frameworks like Apache Kafka, Flink, Spark S
• treamingCollaborate cross-functionally with product, analytics, and AI teams to ensure data is a strateg
• ic assetAdvance ongoing modernization efforts, deepening adoption of event-driven architectures and cloud-native tech
• nologiesDrive adoption of best practices in data governance, observability, and performance tuning for streaming w
• orkloadsEmbed 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 de
• ploymentEstablish 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
• responseFoster a culture of quality through peer reviews, providing constructive feedback and seeking input on your

**own work

Basic Qualif**

• ications: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 dat
• a systemsProven experience driving technical direction and mentoring engineers while delivering complex, high-scale solutions as a hands-on co
• ntributorDeep expertise in streaming and real-time data technologies, including frameworks such as Apache Kafka, Flink, and Spark
• StreamingStrong understanding of event-driven architectures and distributed systems, with hands-on experience implementing resilient, low-latency
• pipelinesPractical experience with cloud platforms (AWS, Azure, or GCP) and containerized deployments for data
• workloadsFluency in data quality practices and CI/CD integration, including schema management, automated testing, and validation frameworks (e.g., dbt, Great Expe
• ctations)Operational excellence in observability, with experience implementing metrics, logging, tracing, and alerting for data pipelines using mod
• ern toolsSolid foundation in data governance and performance optimization, ensuring reliability and scalability across batch and streaming env
• ironmentsExperience with Lakehouse architectures and related technologies, including Databricks, Azure ADLS Gen2, and Ap

**ache Hudi

Other Qualificati**

• ons (OQs):Strong collaboration and communication skills, with the ability to influence stakeholders and evangelize modern data practices within your team and across the or
• ganizationStrong analytical and problem-solvi
• ng mindsetAbility to learn quickly and adapt to new technologies, even when unc
• omfortableSelf-starter who thrives with minimal supervision and collaborates effectively as a t
• eam playerExcellent organizational and critical-think
• ing skillsComfortable leveraging AI tools to accelerate d

**evelopment

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

companies.