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Sr. Data Engineer

Lightcast

Quebec, Quebec, CanadaOn Site

Original Job Summary

About the Role

The Sr. Data Engineer at Lightcast is responsible for designing, building, and maintaining the data infrastructure that supports analytics, machine learning, and enterprise decision-making. This role involves developing scalable big data frameworks and delivering high-performing software solutions that drive measurable outcomes.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines (batch & streaming) for analytics, reporting, and ML.
  • Architect applications and automated tools by translating complex requirements into solutions.
  • Define hardware and software solutions ensuring high performance and scalability.
  • Establish standards for data integration, modeling, and schema design.
  • Optimize SQL queries, monitor pipelines, and ensure data quality and consistency.
  • Implement engineering best practices including version control, CI/CD, testing, and code reviews.
  • Collaborate closely with engineering, analytics, and product teams.
  • Mentor junior engineers and provide cross-team technical support.
  • Evaluate and recommend new tools, frameworks, and technologies.
  • Ensure compliance with data security and governance regulations (GDPR, CCPA).

Education & Experience

Bachelor’s in Computer Science or a related field (Master’s preferred) with 5+ years in data engineering, software engineering, or data science. Must have expert SQL skills, proven Snowflake expertise, and hands-on experience with ETL/ELT pipelines, API/event/log integration, plus proficiency in AWS data services, modern languages (Python preferred) and DBT.

Key skills/competency

  • Data Pipelines
  • SQL Optimization
  • Snowflake
  • ETL/ELT
  • AWS
  • Data Modeling
  • Big Data
  • CI/CD
  • Python
  • Mentoring

How to Get Hired at Lightcast

🎯 Tips for Getting Hired

  • Customize your resume: Tailor skills to data engineering demands.
  • Highlight SQL expertise: Emphasize complex query optimization experience.
  • Showcase big data: Demonstrate scalable pipeline projects.
  • Prepare for interviews: Practice technical and behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review SQL query optimization techniques.
Practice building ETL pipelines.
Study AWS data engineering services.
Work on distributed system projects.

Behavioral Questions

Discuss past team collaboration experiences.
Describe a challenging project problem.
Explain mentorship and leadership styles.
Detail approach to conflict resolution.