Platform Engineer

Zodiac Solutions Inc — Canada · Posted ~3 hours ago

Senior

Skills

AWS data pipelines distributed systems SQL ETL Linux EMR Redshift Airflow

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Summary ✨ AI‑Generated

A platform engineering role focused on designing and supporting scalable data infrastructure. Responsibilities include cloud migration, data warehousing, ETL processes, and distributed system development.

Highlights

Senior platform engineering opportunity focused on cloud modernization, big data systems, and enterprise-scale data platforms.

Description

ob Summary: The ideal candidate will have strong expertise in designing, developing, and supporting scalable data pipelines and distributed systems, along with hands-on experience in Big Data ecosystem tools, AWS services, and real-time data processing. This role involves working on data platform modernization, cloud migrations, Data Warehousing and ETL in a fast-paced enterprise environment. Required Technical Skills: • Cloud Technologies Strong experience in AWS Cloud services: EMR, EC2, S3, VPC, RDS, Redshift AWS Glue, IAM, CloudWatch, CloudFormation Airflow (or AWS Managed Workflows) Databases • Experience working with: Netezza is mandatory SQL-based systems: SQL Server and Postgres SQL Data warehouses: Teradata, Redshift, Netezza ETL Tools • Hands-on experience with:SSIS Programming & Scripting Strong proficiency in: SQL Shell scripting • Good to have: Python Operating Systems • Strong experience in Unix/Linux environments • Key Qualifications10+ years of experience in Data Engineering / Big Data / Platform Engineering Key Responsibilities: • Design, develop, maintain and support scalable data pipelines using Big Data and AWS technologies • Lead and support data platform migration initiatives (On-Prem to AWS Cloud), ideally with Netezza background. • Develop and manage ETL/ELT processes using tools like SSIS, Pentaho, or similar Implement and manage AWS services such as EMR, S3, EC2, Redshift, Glue, and Airflow Build and optimize data workflows and orchestration pipelines using Airflow Work with real-time streaming technologies such as Kafka and Spark Streaming • Perform data ingestion, transformation, and validation from multiple data sourcesOptimize SQL queries for performance and scalability • Monitor system performance, troubleshoot issues, and ensure system reliability • Collaborate with cross-functional teams including developers, architects, and infrastructure teams