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Tiger Brands is hiring a Senior Data Engineer to design, build, and optimize data pipelines and analytical models supporting the FMCG value chain. Day-to-day work spans ERP and supply chain systems, CI/CD with Azure DevOps, enterprise Power BI semantic layers, and SQL Server/SSIS/SSAS data warehousing.
Design, build, and optimize scalable ETL pipelines and data stores for cross-functional analytics teams at FirstRand Bank, working with SQL, Hadoop, Spark, and Kafka while maintaining data warehouse platforms and cross-border data governance.
FirstRand Bank is hiring a Data Engineer in Johannesburg to build and optimize data pipeline architecture, ETL processes, and big data platforms supporting cross-functional analytics teams. Core technologies include SQL, Hadoop, Spark, Kafka, Abinitio, AWS (EC2, EMR, RDS, Redshift), Airflow, and Python/Java.
Senior Data Engineer at Tiger Brands (Africa's largest listed FMCG manufacturer) who designs, builds, and maintains ETL/ELT pipelines and data models using SQL Server, SSIS, SSAS, and Power BI, with CI/CD automation via Azure DevOps, supporting reporting, forecasting, supply chain visibility, and commercial insights.
Senior data engineer at Immunai, an AI-driven biotech in Ramat Gan (hybrid), building scalable data pipelines and warehousing for single-cell, genomic, and clinical data. Day-to-day work centers on Python, SQL, ETL (Spark/Beam), orchestration (Airflow/Dagster), BigQuery, and cloud infrastructure supporting AI/ML teams.
Joins a retail consultancy's business intelligence function to architect, maintain, and troubleshoot internal database structures using Azure data technologies. Remote role with 1 day per month in the office, paying £50,000.
Senior and mid-level data platform engineers design and run Azure/Snowflake-based data platforms (Data Factory, Data Lake, Azure ML, Power BI/Fabric), using Terraform for infrastructure-as-code and Azure DevOps/GitHub Actions CI/CD, with a strong focus on observability. Onsite role near Aldenham, UK, at £100,000 per year.
Leads Lyft's Lakehouse Foundation engineering team in Toronto, owning the foundational data layer — catalog and metadata management, Iceberg/Delta table formats, and data access gateways — that powers analytics, ML, and experimentation company-wide, including a multi-year lakehouse modernization and Unity Catalog migration.
Lead-level developer on RBC's Global Functions Technology team in Toronto, working on large-scale data processing and microservices while shaping architecture and delivering secure, well-tested software. Collaborates with Risk, Finance, and Banking stakeholders using Python/C++, JavaScript, and databases.
A senior data engineer role at Appnovation focused on preparing enterprise domain data for AI agents: building data agents over governed datasets in Databricks and Snowflake, running lakehouse migrations (e.g., Apache Iceberg), and onboarding new data domains with strong governance and data quality. Core stack includes SQL, PySpark, dbt, Airflow, and catalogue/governance tooling.
Cineplex is hiring a Senior Data Engineer to own and evolve customer data platforms like Customer360 and Audience360. Day to day: lead end-to-end data product delivery, design robust data models, build secure lakehouse architectures, mentor engineers, and enable AI-driven segmentation and activation for marketing from a hybrid Toronto office.
Senior Data Engineer on CI Financial's Data, AI & Analytics team, designing and operating scalable ELT/ETL data pipelines, reusable ingestion frameworks, and CI/CD workflows for the data platform. Core stack includes Snowflake, dbt, SQL, and Git-based tooling (Bitbucket, Jenkins), onsite four days a week in Toronto.
Senior Data Engineer on HelloFresh's Growth Alliance (Customer Value Optimization) in Toronto, hybrid with 2-3 days/week in office. You design, build, and operate data pipelines powering pricing, personalization, and CLV forecasting using Python, SQL, PySpark, Kafka, Kubernetes, Airflow, and Databricks on AWS.
Senior Data Engineer at Citi building and maintaining scalable Python-based data pipelines, SQL/ETL-ELT solutions, and data models that power enterprise analytics and BI. Works with relational and NoSQL databases (PostgreSQL/Oracle/MongoDB) and big-data tools like PySpark, Databricks, and Airflow in a regulated financial services environment.
Senior Data Engineer at Citibank in Mississauga building Python-based data pipelines, ETL/ELT frameworks, and data models that power enterprise analytics and BI. Core stack includes Python, SQL (PostgreSQL, Oracle, SQL Server), MongoDB, and PySpark, with Airflow, Databricks/Starburst, and CI/CD tooling.
Senior Data Engineer who owns Cineplex's customer data platforms (Customer360, Audience360, Databricks Customer Lake, Braze integrations), building batch and near real-time pipelines, dimensional models, and audience activation flows on Azure Databricks, Spark/PySpark, SQL, Delta Lake, Azure Data Factory and dbt. Hybrid role: 3 days/week in the Toronto office.
A spatial data engineer (role posted for Esri's ArcGIS geocoding team) who analyzes, enhances, and loads spatial/address data into normalized databases on a regular cadence. Day-to-day work centers on Python and SQL scripting, ETL workflows, and evaluating data sources like Here, TomTom, and OpenStreetMap using ArcGIS tooling.
Data Engineer 2 at JLL in Toronto designs and builds production ETL/ELT data pipelines, CI/CD workflows, and enterprise data solutions for commercial real estate, using Python, SQL, orchestration tools (Airflow, Azure Data Factory), Spark/PySpark, and cloud data services on Azure/AWS/GCP, with AI and automation integrated into the workflows.
Senior Data Engineer on RBC Wealth Management's Technology Data team in Toronto, developing, testing, and deploying data/software architectures and automation to power advanced analytics and ML solutions. Day-to-day involves SQL, Python/Java/TypeScript automation scripts, GenAI-assisted code and testing, and Agile/DevOps practices with tools like JIRA and GitHub.
Principal Data Engineer at BMO in Toronto who oversees enterprise data pipeline architecture, cloud data platforms, and data integration across hybrid cloud/on-premise setups. Requires hands-on coding in Python, Spark, and Scala, plus expertise in big data, streaming, data warehousing, and AI/ML practices (GenAI, RAG, MLOps, LLMOps).
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