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  • Levio

    Data Engineer

    Levio · Canada · posted 1 month ago
    ApplyFull posting

    Extracted from the posting

    Base
    Not stated
    Remote
    Hybrid
    Stack
    Python, Apache Spark, PostgreSQL, AWS

    TL;DR

    Design and build data integration pipelines using Python, SQL Server, Snowflake, and AWS. Role involves ETL development, API/SFTP integrations, and production troubleshooting across data platforms.

    About Levio →

    The full posting

    Are you looking to thrive in a stimulating work environment ? Join the leader in digital transformation and boost your career at Levio. We offer you a unique opportunity to develop your expertise within a high-caliber team. The variety of challenges presented by our clients will give you the opportunity to excel and keep your expertise at its peak. Experience the daily life of our clients and be a significant player in the most ambitious projects in technology and software solutions

    POSITION OVERVIEW

    We are seeking a Data Engineer to design, build, and support data feeds and integration pipelines from the ground up.
    The role will involve integrating data from APIs, SFTP files, databases, and other sources; processing and transforming data using Python and SQL; developing Snowflake data pipelines; and deploying containerized workloads in AWS.
    The ideal candidate is a hands-on data engineer with strong Python, Microsoft SQL Server, and Snowflake experience, along with the ability to troubleshoot production data feeds and work across cloud-based data and integration technologies.

    YOUR RESPONSIBILITIES

    • Design, develop, and maintain data feeds and integration pipelines from source systems through processing and downstream delivery.
    • Build integrations using REST APIs, SFTP, SQL Server, Snowflake, and other data sources.
    • Develop Python applications and scripts for data ingestion, transformation, validation, reconciliation, and processing.
    • Develop and support Snowflake data pipelines, including incremental data-loading patterns and Snowflake-native capabilities such as stages, Snowpipe, Streams, Tasks, and stored procedures.
    • Apply Data Vault modeling principles, including Hubs, Links, Satellites, hash keys, hash differences, and incremental loading.
    • Write and troubleshoot T-SQL for data extraction, transformation, validation, reconciliation, and data processing.
    • Containerize Python-based data-processing applications using Docker and run them as AWS ECS tasks.
    • Monitor and troubleshoot data feeds and pipelines, resolving issues involving APIs, SFTP transfers, data processing, SQL Server, Snowflake, and downstream systems.
    • Implement appropriate error handling, logging, monitoring, and retry mechanisms to support reliable production data feeds.
    • Collaborate with technical and business stakeholders to understand requirements, resolve data issues, and support end-to-end data integration workflows
    • Maintain technical documentation for data pipelines, integrations, data models, and operational procedures..

    REQUIRED QUALIFICATIONS

    • Production experience developing data feeds, data integrations, or data pipelines.
    • Strong Python development experience, including data processing and transformation.
    • Strong hands-on experience with Microsoft SQL Server and T-SQL, including complex queries, joins, CTEs, aggregations, data manipulation, views, and stored procedures.
    • Hands-on experience with Snowflake, including data querying, loading, transformation, validation, and pipeline development.
    • Experience with Data Vault modeling, including Hubs, Links, Satellites, hash keys, hash differences, and incremental data-loading patterns.
    • Experience developing and supporting Snowflake pipelines using stages, Snowpipe, Streams, Tasks, and stored procedures.
    • Hands-on experience integrating with REST APIs, including authentication, response handling, error handling, and pagination.
    • Hands-on experience with SFTP/file-based data integrations.
    • Experience processing structured data such as JSON, CSV, and XML.
    • Basic working knowledge of Docker, including containerizing applications.
    • Basic working knowledge of AWS ECS and running containerized workloads as ECS tasks.
    • Strong troubleshooting and problem-solving skills, particularly in production data and integration environments.
    • Familiarity with version control and standard software development lifecycle practices

    PREFERRED QUALIFICATIONS

    • Experience with AWS services, particularly ECS, S3, CloudWatch, IAM, and Secrets Manager.
    • Experience with Kafka or similar event-streaming/message-broker technologies.
    • Experience with CI/CD pipelines for building, testing, security scanning, and deploying Python and containerized applications.
    • Experience with CI/CD tools such as Harness, GitHub Actions, GitLab CI, Jenkins, or similar platforms.
    • Experience working with MongoDB, including querying, ingesting, updating, and processing data from MongoDB collections as part of data integration workflows.
    • Experience with infrastructure-as-code tools such as Terraform or CloudFormation.
    • Experience implementing data-quality, validation, reconciliation, monitoring, alerting, and operational support processes.
    • Familiarity with AWS networking and security concepts
    • Experience working in an Agile/Scrum development environment.

    WHAT SUCCESS LOOKS LIKE

    The successful candidate will be able to take a data-feed requirement from source to production, developing the necessary Python processing and integrations, working with SQL Server and Snowflake, applying appropriate data
    modeling and incremental-loading patterns, containerizing the solution, and deploying it through AWS.

    They will also be able to independently troubleshoot production issues across the end-to-end workflow:
    API / SFTP / Database / Event Stream - Python Processing - SQL Server / Snowflake / MongoDB - AWS ECS - Downstream Systems

    The candidate should be comfortable working independently, collaborating across technical teams, and taking ownership of the reliability and ongoing operation of the data pipelines they build.

    BENEFITS AND WORK ENVIRONMENT

    Levio offers a comprehensive and flexible benefits package designed to support your professional growth and personal wellbeing, including: 

    • 4 weeks of cumulative vacation starting from day one 
    • Flexible working hours 
    • Professional Development Allowance (PDA) for training, computer equipment, and physical activities 
    • Training tailored to your areas of expertise 
    • Registered Retirement Savings Plan (RRSP) with employer contribution up to 3% of gross salary 
    • Modular group insurance plan
    • Public transportation or parking reimbursement when required 
    • Referral bonuses 
    • 11 statutory holidays 
    • Personal days 
    • An active social life (5to7 events, social club, healthy snacks, coffee, and more) 

    • Employment type: Full time, permanent 

    Employment Equity 

    Levio subscribes to the principle of employment equity and applies an equal access employment program for women, Indigenous peoples, visible minorities, ethnic minorities, and persons with disabilities. 

    We value diversity and inclusion and are committed to creating a healthy, accessible, and rewarding work environment that highlights the unique contributions of our employees. Accommodations are available upon request for candidates participating in all aspects of the selection process.