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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

Not detected in the job text

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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