Job Title: Big Data Developer – Spark, AWS, Airflow & Snowflake


Company: Cogency Inc.


Location: Greater Toronto Area, ON


Work Model: Hybrid – 4 Days Onsite


Job Type: Full-Time


Job Summary


Cogency Inc. is seeking a skilled Big Data Developer / Data Engineer with strong expertise in Spark, Snowflake, AWS, Airflow, Big Data technologies, and ETL . The successful candidate will design, develop, and optimize scalable data pipelines and ETL processes while ensuring data quality, security, reliability, and performance.

The role involves working closely with cross-functional teams in an Agile environment to deliver robust data solutions supporting analytics, reporting, and business intelligence initiatives.


Key Responsibilities


  • Design, develop, and maintain scalable data ingestion pipelines and ETL workflows .
  • Build and optimize data pipelines, transformation frameworks, and processing workflows.
  • Develop and optimize Apache Spark applications for large-scale data processing.
  • Work with Hadoop, Spark, and Hive within Big Data environments.
  • Design and optimize Snowflake data solutions, data models, and SQL workloads.
  • Develop complex SQL queries, stored procedures, transformations, and data models.
  • Integrate Snowflake with enterprise data sources and BI/reporting platforms.
  • Develop ETL workflows using Informatica, Talend, Apache Airflow , or similar technologies.
  • Build and manage workflow orchestration using Apache Airflow .
  • Develop data solutions on AWS , leveraging services such as S3, Glue, and Lambda.
  • Monitor, troubleshoot, and resolve data pipeline and platform performance issues.
  • Implement data quality, integrity, security, and governance controls.
  • Develop APIs and data integrations using Scala or Java .
  • Implement CI/CD, DevSecOps, and Infrastructure-as-Code practices.
  • Maintain technical documentation for data pipelines, transformations, and data models.
  • Collaborate with Data Architects, Developers, DevOps teams, Business Analysts, and other stakeholders.
  • Participate in Agile ceremonies, code reviews, testing, deployment, and production support.
  • Leverage GenAI and AI-assisted development tools to improve developer productivity and code quality.


Required Skills & Experience


  • 5+ years of experience in Data Engineering, Big Data, or ETL development.
  • Strong hands-on experience with:
  • Apache Spark
  • Hadoop
  • Hive
  • Snowflake
  • Strong SQL and data modeling skills.
  • Programming experience in Scala or Java .
  • Experience developing APIs and enterprise data integrations.
  • Experience with ETL technologies such as Informatica, Talend, or Apache Airflow .
  • Strong understanding of data ingestion, transformation, processing, and pipeline optimization.
  • Experience working with cloud platforms, preferably AWS .
  • Understanding of CI/CD, DevSecOps, and Infrastructure-as-Code practices.
  • Experience working in Agile delivery environments.
  • Strong troubleshooting, analytical, and problem-solving skills.
  • Excellent communication and collaboration skills.


Preferred / Nice-to-Have


  • Hands-on experience with AWS Glue, S3, Lambda , and other AWS data services.
  • Strong experience with Apache Airflow or similar orchestration platforms.
  • Experience with GitHub Actions, Git, and automated testing .
  • Knowledge of Python or other scripting languages.
  • Experience with Shell/Bash scripting.
  • Exposure to Docker, Kubernetes, or OpenShift .
  • Experience with Infrastructure-as-Code tools such as Terraform.
  • Experience with GenAI tools for code generation, code review, and developer productivity.


Education


  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline .


Key Competencies


  • Big Data Engineering
  • Apache Spark
  • Snowflake
  • AWS Cloud
  • ETL/ELT Development
  • Data Pipeline Engineering
  • Apache Airflow
  • SQL & Data Modeling
  • Scala / Java
  • API Integration
  • DevSecOps & CI/CD
  • Data Quality & Governance
  • Agile Delivery
  • Problem Solving & Troubleshooting


Work Model: Greater Toronto Area – 4 Days Onsite per Week

Employment Type: Full-Time

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