Databricks Developer

Toronto, ON, Canada

$75 to $77 CAD / hour · Contract

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Job details

Pay: $75 to $77 CAD / hour
Job type: Contract
Apply by: Dec 10, 2026
Posting language: English
Posted: Nov 10, 2026

Original job description

Are you a hands-on Databricks Developer ready to build scalable data solutions? Apply Now!

Working with one of our top financial clients, this role calls for a Databricks Developer to design, develop, and optimise enterprise-grade data pipelines using Databricks and Apache Spark. This six-month contract offers the opportunity to work with large-scale datasets, contribute to solution design, collaborate with business and technology stakeholders, and apply advanced data engineering practices in a fast-paced environment. Banking or financial services experience is highly preferred.

Pay rate range (CAD): $75.00/hr – $77.00/hr

Responsibilities

Design, develop, and optimise data pipelines using Databricks and Apache Spark.
Build scalable ETL pipelines supporting batch processing, Auto Loader, and Spark Structured Streaming.
Develop and maintain end-to-end data environments, including catalogs, schemas, tables, materialised views, functions, and volumes.
Implement slowly changing dimensions using SCD 1 and SCD 2 methodologies.
Build and support change data capture pipelines.
Use Unity Catalog to manage data governance and access across data environments.
Develop Lakehouse Federation solutions and create foreign catalogs for external data sources.
Apply Databricks partitioning and liquid clustering techniques to improve performance.
Work with large-scale datasets in distributed computing environments.
Collaborate with cross-functional teams and business stakeholders to understand requirements and deliver effective solutions.
Contribute to solution design discussions and provide practical technical recommendations.
Ensure data quality, performance, scalability, and reliability across delivered solutions.
Communicate technical concepts clearly to stakeholders at varying levels of technical expertise.

Desired Skill-Set

Strong hands-on experience developing solutions with Databricks and Apache Spark.
Experience with Azure Databricks or Delta Lake.
Proven experience building batch and streaming ETL pipelines using Auto Loader and Spark Structured Streaming.
Strong hands-on experience with Unity Catalog.
Experience creating catalogs, schemas, tables, materialised views, functions, and volumes.
Experience implementing SCD 1 and SCD 2 solutions for dimension tables.
Experience developing change data capture pipelines.
Strong experience with Lakehouse Federation and foreign catalogs.
Strong understanding of Databricks partitioning and liquid clustering.
Experience working in enterprise environments; banking or financial services experience is preferred.
Strong communication and stakeholder management skills.
Ability to work independently and effectively in a fast-paced environment.

Nice to Have

Experience with Kafka.
Experience with Python.

BeachHead is an equal opportunity agency and employer. We advocate for our candidates and welcome applicants regardless of race, color, religion, national origin, sex, age, or physical or mental disability. BeachHead or our clients may use technology-enabled tools, including automation and artificial intelligence (AI), to support parts of the recruitment process such as resume screening, application management, and candidate matching. These tools assist our recruiters and our clients, and do not replace human decision-making. This job posting represents a current or anticipated vacancy. The position may be filled at any time, and the posting may be removed without notice once the role has been filled.

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More about this job

Responsibilities

Design, develop, and optimize scalable batch and streaming data pipelines and end-to-end Databricks environments, including governance, change data capture, and dimensional data solutions. Collaborate with stakeholders on solution design and ensure delivered systems meet data quality, performance, scalability, and reliability needs.

Requirements

Requires strong hands-on experience with Databricks and Apache Spark, including batch and streaming ETL, Unity Catalog, SCD 1 and SCD 2, change data capture, and Lakehouse Federation. Enterprise experience and strong communication skills are expected; banking or financial services experience is preferred, while Kafka and Python are nice to have.

Skills

Databricks
Apache Spark
Azure Databricks
Delta Lake
ETL Pipelines
Auto Loader
Spark Structured Streaming
Unity Catalog
Slowly Changing Dimensions
Change Data Capture
Lakehouse Federation
Foreign Catalogs
Data Partitioning
Liquid Clustering
Python
Kafka

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Apache Spark
Azure Databricks
Delta Lake
Data Engineering
ETL
Batch Processing
Auto Loader
Spark Structured Streaming
Unity Catalog
Data Governance
Catalogs
Schemas
Tables
Materialized Views
Functions
Volumes
SCD 1
SCD 2
Change Data Capture
Lakehouse Federation
Foreign Catalogs
Partitioning
Liquid Clustering
Distributed Computing
Kafka
Python
Banking
Financial Services

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