Data Engineer – Databricks & MDM
- Toronto, ON, Canada
Contract
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Job details
- Job type
- Contract
- Apply by
- 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