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Added 6 hours ago
AI
Senior AWS Data Engineer
Apptoza Inc.
Toronto, ON
- Full-time
We are seeking a Senior AWS Data Engineer with 12+ years of hands-on experience designing, developing, and supporting enterprise-scale data platforms on AWS. The ideal candidate will be a…
Added 6 hours ago
RC
Senior Data Engineer
RSM Canada
Calgary, AB
- Full-time
…instill confidence in a world of change, empowering our clients and people to realize their full potential. Our exceptional people are the key to our unrivaled, inclusive culture and talent…
Added 6 hours ago
CT
Lead/Senior Data Engineer
Celebal Technologies
Ottawa, ON
- Contract
Design, develop, test, and maintain scalable ETL/ELT pipelines using Databricks, Spark, SQL, Python, and AWS.
Added 10 hours ago
V
Lead Software Engineer
Virtusa
Toronto, ON
- Full-time
Job Summary: The IMS Production Support L3 Engineer is responsible for ensuring the stability, availability, and performance of applications across AMS, Cloudera, and on-premises…
Added 11 hours ago
H
Senior WMS Implementation Engineer
Hays
Canada
- $95 to $100 CAD / hour
- Contract
Proficient in Python for data science and GenAI application development
Added 11 hours ago
L
Applied AI Engineer
Luxoft
Canada
- Full-time
Our client is an energy solutions provider. Our AI-enabled platform supports operations, tracking and decision-making to optimize large-scale renewable and traditional energy portfolios.…
Added 12 hours ago
P
Associate Data Engineer
Punt
Vancouver, BC
- $80,000 to $100,000 CAD / year
- Full-time
Above all, we value strong SQL fundamentals, working Python proficiency, and the instinct to double-check your output for correctness before someone else has to.
Added 14 hours ago
T
Site Reliability Engineer Lead
TD
Toronto, ON
- Full-time
We are seeking an experienced Site Reliability Engineer Lead, you will lead the delivery, operation, modernization, and lifecycle management of cloud, database, analytics, and…
Added 15 hours ago
S
Data & AI Engineer - Real World Data and Healthcare Intelligence
Sanofi
Toronto, ON
- Full-time
Developing and managing microservices using python

Celebal Technologies

Lead/Senior Data Engineer

Ottawa, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 29, 2026
Posting language: English
Posted: Oct 30, 2026

Original job description

Senior/Lead Data Engineer

Duration: Long Term

Location: Ottawa, ON K2J 0P7

Role Summary

Our client is seeking an experienced, hands-on Senior Data Engineer to help build and scale the enterprise data foundation supporting Analytics, AI, and self-service decision-making across the company.

This role requires more than just moving data between systems. The successful candidate will act as a data product architect, transforming complex, messy operational data into trusted, reusable, business-ready data products. These products will power enterprise analytics, Tableau reporting, Databricks Genie / Genie Code, machine learning, and emerging GenAI use cases across Manufacturing, Supply Chain, Sales, Finance, and HR.

You will play a pivotal role in shifting the organization away from one-off, siloed pipelines toward a highly governed, centralized single-source-of-truth platform built entirely on Databricks and AWS.

Key Responsibilities:

1. Data Engineering & Lakehouse Development

Design, develop, test, and maintain scalable ETL/ELT pipelines using Databricks, Spark, SQL, Python, and AWS.
Build and maintain lakehouse solutions leveraging Delta Lake and Medallion Architecture (Bronze, Silver, Gold).
Integrate structured and semi-structured data from enterprise applications, manufacturing systems, databases, APIs, and cloud operational sources.
Optimize Databricks workloads, SQL queries, Delta tables, compute utilization, and end-to-end pipeline performance.
Implement orchestration, monitoring, error handling, data reconciliation, and automated recovery for production data pipelines.

2. Enterprise Data Modeling & Data Products

Design scalable enterprise data models (dimensional modeling, star schemas, fact/dimension structures) supporting cross-functional analytics and standardized KPIs.
Transform raw operational data into curated, business-ready data products that can be reused across dashboards, analytics, AI, and ML applications.
Collaborate closely with business and analytics teams to translate complex business definitions into technically robust data models.

3. Analytics AI & Self-Service Enablement

Build AI-ready and Genie-ready data products that allow business users to securely analyze enterprise data using Databricks Genie and Genie Code.
Structure data, metadata, relationships, business definitions, and semantic/contextual layers to maximize the accuracy of conversational AI analytics.
Enable engineers, analysts, and business users to perform governed self-service analysis without creating uncontrolled copies of data.
Partner with data science teams to prepare feature-ready datasets for predictive analytics, machine learning, and MLOps workloads.

4. Data Governance, Quality & DataOps

Implement data governance, cataloging, lineage, metadata management, and role-based access controls using Databricks Unity Catalog.
Build automated data-quality checks for completeness, accuracy, consistency, freshness, and cross-system reconciliation.
Apply Git-based development, code reviews, testing, version control, and automated CI/CD processes for Databricks assets.
Focus heavily on developing reusable engineering frameworks and templates rather than building hard-coded, one-off pipelines.

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More about this job

Responsibilities

Build and optimize scalable Databricks and AWS lakehouse pipelines, and transform operational data into governed, reusable data products for analytics, AI, and machine learning. Establish enterprise data models, self-service analytics capabilities, data governance and quality controls, and reusable engineering and CI/CD frameworks.

Requirements

The role calls for a hands-on senior or lead data engineer with strong experience in Databricks, Spark, SQL, Python, AWS, and scalable ETL/ELT pipeline development. Candidates should be able to design enterprise data models and governed data products, optimize production workloads, and support analytics, AI, and machine learning use cases.

Skills

Databricks
Apache Spark
SQL
Python
AWS
ETL/ELT
Delta Lake
Medallion Architecture
Data Modeling
Data Governance
Unity Catalog
Data Quality
CI/CD
DataOps
Machine Learning
Data Orchestration

Visa sponsorship

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Keywords

Databricks
Apache Spark
SQL
Python
AWS
ETL/ELT
Lakehouse
Delta Lake
Medallion Architecture
Enterprise Data Modeling
Dimensional Modeling
Star Schema
Data Products
Databricks Genie
Genie Code
Tableau
Unity Catalog
Data Governance
Data Cataloging
Data Lineage
Metadata Management
Role-Based Access Control
Data Quality
CI/CD
Git
Machine Learning
MLOps
Data Orchestration
Manufacturing Data
Self-Service Analytics

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