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Data Engineer – Databricks & MDM

  • Toronto, ON, Canada

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Job details

Job type
Contract
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Experience
5+ years of professional experience in data engineering or a closely related data integration role.
Posting language
English
Posted

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.
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

Categories

  • Data & Analytics
  • Technology
  • Software
  • Engineering

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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