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Teqfocus

Data Engineer – Databricks & MDM

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Dec 5, 2026
Experience: 5+ years of professional experience in data engineering or a closely related data integration role.
Posting language: English
Posted: Nov 5, 2026

Original job description

Role Overview:

We are seeking a hands-on Data Engineer with 5+ years of experience to support data engineering and master data management initiatives. The ideal candidate brings practical Databricks expertise, strong experience working with structured and semi-structured data (particularly JSON), and hands-on exposure to Reltio MDM. This is an initial three-month contract with a strong possibility of extension based on project needs and performance.

About Teqfocus:

Teqfocus is a Data and AI company that helps enterprises build and scale the Agentic Enterprise - connecting the data foundation, the intelligence layer, and the applications teams run their businesses on into a single, coherent architecture.

As a Salesforce Summit Partner, we work in Healthcare, Life Sciences, Financial Services, Insurance, and Hi-Tech - industries where getting AI right matters and the tolerance for failure is low. Our delivery model is senior-heavy by design. The same team that scopes an engagement ships it to production. There are no junior shadow teams, no sub-contractors brought in when the problem gets hard, and no hand-off to a separate managed services vendor when the project closes.

We run an internal innovation practice that builds the reusable patterns, pre-tested architectures, and industry-specific frameworks that give every Teqfocus client a head start - and give every Teqfocus practitioner work that compounds over time.

We are a diverse, immigrant-entrepreneurial company. We were built on the conviction that the best outcomes come from people who take genuine ownership of what they build - and are trusted to do so.

www.teqfocus.com

Key Responsibilities:

Design, develop and maintain reliable data ingestion, transformation and processing pipelines using Databricks and SQL/Python-based tooling.
Process, parse, transform and validate structured and semi-structured datasets, including nested JSON payloads from source systems and APIs.
Work with Reltio MDM data models, records and integrations to support master data quality, synchronization and downstream consumption.
Implement data mapping, cleansing, deduplication, reconciliation and validation checks to improve accuracy and consistency.
Collaborate with analysts, architects and application teams to translate source-to-target requirements into robust data solutions.
Troubleshoot pipeline failures, data discrepancies and performance bottlenecks; document mappings, assumptions and operational handoffs.

Required Skills & Qualifications:

5+ years of professional experience in data engineering or a closely related data integration role.
Hands-on experience with Databricks for data processing, transformations and pipeline development.
Strong proficiency in SQL and working knowledge of Python and/or PySpark.
Practical experience handling JSON data, including nested structures, schema mapping, parsing and transformation.
Working experience with Reltio MDM, including master data concepts such as entities, relationships, match/merge and data quality.
Ability to integrate, validate and troubleshoot data across multiple source and target systems.
Strong communication skills and ability to contribute effectively within a hybrid delivery team.

Good to Have:

Experience with Delta Lake, Spark performance tuning and Databricks workflows/jobs.
Experience integrating REST APIs or cloud-based data platforms.
Familiarity with data governance, metadata management and MDM survivorship rules.

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More about this job

Responsibilities

Design, build, and maintain Databricks-based data pipelines, processing structured and semi-structured data such as nested JSON. Support Reltio MDM data quality and integrations, implement mapping and validation processes, and troubleshoot data and pipeline issues in collaboration with cross-functional teams.

Requirements

Requires 5+ years of data engineering or related data integration experience, hands-on Databricks expertise, strong SQL skills, and working knowledge of Python and/or PySpark. Candidates should have practical experience with nested JSON and Reltio MDM concepts, and be able to integrate, validate, and troubleshoot data across systems.

Skills

Databricks
SQL
Python
PySpark
JSON
Reltio MDM
Data Engineering
Data Integration
Data Pipelines
Data Transformation
Data Mapping
Data Cleansing
Data Deduplication
Data Validation
Master Data Management
REST APIs

Visa sponsorship

Not detected in the job text

Keywords

Databricks
SQL
Python
PySpark
JSON
Reltio MDM
Master Data Management
Data Engineering
Data Integration
Data Ingestion
Data Transformation
Data Processing
Data Pipelines
Delta Lake
Apache Spark
Spark Performance Tuning
Databricks Workflows
Databricks Jobs
REST APIs
Cloud Data Platforms
Data Mapping
Data Cleansing
Deduplication
Data Reconciliation
Data Quality
Data Governance
Metadata Management
Survivorship Rules
Match and Merge
Source-to-Target Mapping

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