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Added 6 days ago
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Principal Data Architect
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Strong Python scripting and automation capabilities.
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Principal Application Security Specialist
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Full-time
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Added 6 days ago
Solutions Architect
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Contract
Hands-on development experience in Java, Python, C#, or C++.
Added 7 days ago
PySpark / Databricks Developer (Junior to Intermediate)
Electric Mind
Toronto, ON
Full-time · Contract
We're looking for a developer to help build and maintain data pipelines on Databricks for a financial services / wealth management data platform. The platform ingests data from multiple…
Added 6 days ago
QA Automation Engineer
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Full-time
Proficiency in Java, Python, JavaScript, or C#

Electric Mind

PySpark / Databricks Developer (Junior to Intermediate)

Toronto, ON, Canada

Job type: Full-time · Contract
Posting language: English
Posted: Sep 18, 2026

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Original job description

At Electric Mind, Engineering is where strategy meets action. Our team helps organizations cut through complexity - aligning business ambition with technology execution to unlock real, lasting change. You’ll work alongside curious, driven people tackling high-impact challenges for everyone from scaling startups to global enterprises. Each engagement is different, pushing you to learn, adapt, and grow.

Electric Mind’s Technology Practice brings together deep engineering expertise, modern delivery disciplines, and pragmatic architectural thinking to help clients execute complex, mission-critical transformation. We design and implement scalable, secure, high-impact technology solutions that accelerate business outcomes.

About the Role

We're looking for a developer to help build and maintain data pipelines on Databricks for a financial services / wealth management data platform. The platform ingests data from multiple source systems, transforms it through a medallion architecture (bronze → silver → gold) using PySpark, and publishes curated data to downstream consumers via file exports and Kafka. You'll work alongside a senior engineer, writing transform code, fixing pipeline issues, and helping keep the environment healthy across dev/qa/uat.

This is a good fit for someone with solid Python fundamentals and some Spark/SQL exposure who wants to grow into a data engineering specialist. You won't be expected to know Databricks internals on day one - you will be expected to learn fast, ask good questions, and write clean,

\nWhat You'll Work On

Writing and maintaining PySpark transforms (hand-written, not a generic framework) for silver and gold layer tables - things like customer, account, and transaction data models.
Working with Lakeflow Declarative Pipelines (Databricks' current pipeline framework - successor to DLT) and Auto CDC / SCD Type 2 patterns for change-data-capture merges.
Querying and validating data in Unity Catalog across environments (dev/qa/uat) using SQL warehouses.
Debugging failed pipeline runs: reading pipeline event logs, tracing bad records, fixing schema drift or data quality issues.
Maintaining reference/lookup tables and small utility scripts (PowerShell/Python) used to operate the platform.
Writing and updating unit/integration tests for transform logic.
Participating in code review, using Git feature branches and merge requests (GitLab).
Keeping documentation current when you change how something works.

Must-Have Skills

Python - comfortable writing clean, readable code; understands functions, modules, basic OOP.
Some exposure to Apache Spark / PySpark, or strong SQL skills plus a willingness to learn Spark quickly.
Working knowledge of SQL (joins, aggregations, window functions).
Basic Git workflow: branches, commits, pull/merge requests.
Comfortable reading other people's code and stack traces, and debugging methodically (not guess-and-check).

Nice-to-Have Skills

Direct experience with Databricks (notebooks, jobs, clusters, or SQL warehouses).
Familiarity with Delta Lake, medallion architecture (bronze/silver/gold), or CDC/SCD concepts.
Exposure to Azure (this environment runs on Azure Databricks with Azure AD service principal auth).
Experience with Kafka or other streaming/event systems.
Experience with CI/CD pipelines (this project uses GitLab CI).
Prior work in financial services or a regulated data environment.

What Success Looks Like in the First 90 Days

Can independently pick up a small transform bug or enhancement ticket, make the change, test it, and open a merge request.
Comfortable running existing operational scripts to check pipeline status, query tables, and diagnose failures without hand-holding.
Starting to take ownership of the Databricks environments and help write new transforms

About Electric Mind

Electric Mind is a fast-growing, AI-native advisory and digital engineering firm built for those who want to shape the future, not just watch it happen. We blend premium strategy expertise with cutting-edge AI-centric engineering to solve complex, meaningful problems for industry-leading clients.

We pride ourselves on a high-touch delivery model and a culture that values diverse talent, innovation, and true client partnership - creating an environment where your ideas matter and your impact is visible.

If you’re looking for a place where you can grow fast, collaborate with exceptional teammates, and help build a company scaling its capabilities and global footprint at speed - Electric Mind is the place to ignite your career. The future is bright!

For more info on Electric Mind, check out our Careers Page and Instagram.

Electric Mind is committed to diversity in the workplace. We are an inclusive employer and welcome and encourage applications from all qualified candidates. Applicants’ needs will be accommodated during our recruitment and selection process so please advise us if you require accommodation.

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More about this job

Responsibilities

You will build and maintain data pipelines on Databricks using PySpark to transform data through a medallion architecture. Additionally, you will debug pipeline issues, validate data in Unity Catalog, and write unit tests for transform logic.

Requirements

The role requires solid Python fundamentals, experience with SQL, and a willingness to learn Spark quickly. Candidates should also have basic Git workflow knowledge and the ability to debug code methodically.

Skills

Python
PySpark
Databricks
SQL
Git
Delta Lake
Medallion Architecture
Azure
Kafka
CI/CD
GitLab
Data Pipelines
Unity Catalog
Change Data Capture
Data Modeling
Unit Testing

Visa sponsorship

Not detected in the job text

Keywords

PySpark
Databricks
Data Engineering
Python
SQL
Delta Lake
Medallion Architecture
Azure
Kafka
Git
GitLab
CI/CD
Unity Catalog
Data Pipelines
Financial Services
Wealth Management
Change Data Capture
SCD Type 2
Data Quality
Schema Drift
PowerShell
Unit Testing
Integration Testing
Azure AD
Lakeflow
Data Modeling
Software Engineering
Cloud Computing
Data Platform
Consulting

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