Remote Data Jobs · SQL

We are looking for a Data Engineer passionate about technology and with expertise in building and maintaining robust and scalable data pipelines. You will be a technical reference in Oracle and PowerCenter, ensuring quality, governance, and end-to-end performance in the team's pipelines and dimensional model. Expertise in Databricks and PySpark is a valuable differential.

The job involves being responsible for data ingestion, analysis, and migration, with a focus on Business Intelligence and data engineering. The candidate will develop, optimize, and maintain ETL/ELT pipelines to migrate data from various sources using PostgreSQL. They will also analyze and understand business requirements, transforming insights into actions.

You'll play a crucial role in developing and maintaining scalable data pipelines and infrastructure to drive data analytics and machine learning solutions for our clients. Design and create robust, scalable data pipelines using Databricks, Apache Spark, and SQL to transform and process large datasets efficiently. You will collaborate with data architects to design data models and architecture that support data analytics and machine learning applications.

Help manage the data platform, extend its impact to best support critical data workflows. Build, test, document, and deploy reliable data pipelines, working with diverse systems. Proactively contribute to the evolution of the Data Analytics Platform by proposing new ideas and exploring innovative big data tools.

Design, implement, and maintain scalable data pipelines using Snowflake, Coalesce.io, Airbyte, and SQL Server/SSIS, with some use of Azure Data Factory. Build and maintain dimensional data models to ensure high-quality, structured data for analytics and reporting. Implement Medallion architecture in Snowflake, managing bronze, silver, and gold layers. Collaborate with teams using Jira for task tracking and GitHub for code repository management.

Lead, coach, and mentor a high performing team of data scientists, analysts, and associates dedicated to Finance data science and Market risk initiatives. Deliver high-quality financial metrics and advanced analytics to support key decisions related to financial planning, treasury operations, and liquidity management. Develop and maintain the finance data mart, with a focus on optimizing data quality, accessibility, and efficiency.

The Analytics Consulting position will provide client consultation for analytical consulting engagements, including decision tool and strategy implementation and monitoring, statistical scoring validation, business intelligence, data quality, and analytical product / solution development for consumer solutions. Topics include optimization strategies, model development and usage and business intelligence consulting around portfolio profiling, market share and credit risk analysis. This is a fully remote position.

You will be responsible for building robust, efficient and integrated data models that enable our fraud analytics and machine learning. These core data models will serve as the foundation of our fraud strategy, allowing the team to monitor and detect fraud trends, build machine learning models, and launch new fraud defenses. In this role, you will have the opportunity to: Build data models in the cloud data warehouse that will be used as the source of truth for analytics and predictive modelling.

You will be responsible for the design and execution of product experiments and building robust machine learning pipelines to build the flagship personalization framework at Wealthsimple. Blend expertise in experimental design, predictive modelling and software engineering while effectively communicating with stakeholders.

You'll play a key role in designing, building, and maintaining the systems that power our analytics, personalization, and financial insights. You’ll collaborate closely with product and engineering to ensure that high-quality, reliable data drives every decision we make and every experience we deliver.