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Data Engineer

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Onsite

Data Engineer

Fynite Corp.

Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonData ScienceSnowflakeAmazon RedshiftData AnalysisMachine LearningAIAWSApache AirflowComplianceAzure

14 days ago

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Important information


Contract type:

Freelance / Contract

Location:

Canada

Work mode:

Onsite

Published on:

7 October 2026

What they need


Location: Remote

Type: Full-Time

Company: Fynite

About the Role:

Fynite is looking for a Data Engineer to design and scale data pipelines that power enterprise AI systems and high-performance analytics workloads.

This role combines data pipeline engineering, cloud data platforms, advanced SQL optimization, and Python development to ensure reliability, scalability, and performance across large production datasets. You will work at the intersection of data infrastructure, ETL systems, and performance engineering to support business-critical and AI-driven workflows.

Key Responsibilities:

Data Engineering & Pipelines

  • Design, build, and maintain scalable ETL/ELT pipelines
  • Develop and maintain Python-based scripts and components for data ingestion, transformation, validation, and automation
  • Use Python to process large datasets, integrate APIs and data sources, and troubleshoot complex data issues
  • Validate, transform, and troubleshoot data flows across systems
  • Ensure seamless data integrations and cross-platform data movement
  • Collaborate with engineering and product teams to translate business requirements into scalable data solutions

SQL & Data Platform Optimization

  • Design and optimize complex SQL queries for analytics and operational use cases
  • Work with large-scale datasets and high-volume production workloads
  • Analyze query execution plans and improve performance using indexing, partitioning, and schema optimization
  • Monitor and fine-tune database performance to ensure efficiency and scalability

Database & Governance

  • Manage relational databases ensuring data integrity, accuracy, and availability
  • Develop and maintain database objects (stored procedures, views, functions)
  • Implement data governance standards and ensure compliance with company policies

Required Skills:

  • 5+ years of experience in data engineering, SQL development, or database optimization
  • Strong proficiency in SQL (joins, CTEs, window functions, subqueries)
  • Experience building and supporting ETL/ELT pipelines
  • Strong hands-on experience with data pipeline creation and development
  • Strong hands-on Python experience is required
  • Experience using Python for data engineering, ETL/ELT development, data processing, automation, API integrations, and troubleshooting
  • Ability to write clean, maintainable Python code for production data workflows
  • Experience working with large datasets and high-volume production workloads
  • Strong knowledge of query performance tuning and execution plan analysis
  • Experience managing relational databases in production environments
  • Experience ensuring reliable data integrations across systems

Preferred Skills:

  • Experience with cloud databases (AWS RDS, Azure SQL, BigQuery, Redshift)
  • Data warehousing experience (Snowflake, Redshift, BigQuery)
  • Experience with ETL orchestration tools (Airflow, AWS Glue)
  • Experience with AWS, Azure, or GCP
  • Experience supporting AI/analytics workloads

AI & Agentic Systems (Strongly Preferred):

  • Experience working with AI/ML data pipelines
  • Familiarity with LLM-based systems (OpenAI, Gemini, Bedrock, etc.)
  • Understanding of AI agents, autonomous workflows, or agent orchestration frameworks
  • Hands-on experience building AI agents or agentic workflows is preferred
  • Experience preparing, validating, or optimizing datasets for AI-driven decision systems
  • Exposure to building or supporting data infrastructure powering AI applications

Education

Bachelor’s or Master’s Degree in Computer Science, Data Science, Mathematics, or related field (Master’s preferred)

Why Join Fynite

  • Build data systems that power real AI agents running enterprise workflows
  • Work on a platform combining data, intelligence, and execution end-to-end
  • High-impact role in a fast-scaling AI automation company

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