Data Engineer Lead

1 week ago

Markham, Ontario, Canada Wireframe Solutions-IT Consulting Company Full time $120,000 - $200,000 per year

Must Have skills:

  1. Snowflake
  2. dBT
  3. AWS

Key Responsibilities

  • Technical Leadership: Define and drive the data engineering strategy, standards, and best practices across the organization.
  • Solution Design: Develop high-level and low-level solution architectures, ensuring alignment with business and technical goals.
  • Data Pipeline Development: Lead the design and implementation of high-performance data pipelines using tools like dbt Core/Cloud, ensuring scalability and maintainability.
  • Data Modeling: Design and review conceptual, logical, and physical data models to support business needs.
  • Code Ownership: Write and maintain clean, reusable code in SQL, Python, Shell, and Terraform.
  • Quality & Governance: Champion data quality, governance, and cataloging practices; create and review test plans to validate data solutions.
  • Issue Resolution: Perform root cause analysis and implement effective solutions for complex data issues.
  • Agile Delivery: Lead agile ceremonies, foster a delivery-focused mindset, and ensure timely execution of data initiatives.
  • Mentorship: Guide and mentor Data Engineers and project team members, elevating team capabilities and engineering excellence.
  • Collaboration: Work closely with architects, designers, QA engineers, and delivery teams to ensure cohesive and customer-centric data products.
  • Documentation: Produce and maintain comprehensive technical documentation to support implementation and knowledge sharing.
  • Talent Development: Contribute to hiring by designing technical challenges, conducting interviews, and supporting onboarding.

What you'll bring

Extensive Experience:

  • 15+ years of professional experience delivering over 10 high-impact data projects from inception through warranty.
  • 5+ years of Snowflake, dbtCore/Cloud, and AWS Cloud Technologies.
  • 7+ years of experience with coding in multiple programming languages such as Python, Java, etc.

Technical Expertise:

Deep knowledge of relational databases (Snowflake, PostgreSQL, Amazon Aurora), big data platforms (Hadoop), and NoSQL databases (e.g., MongoDB).

Data Visualization Proficiency:

Skilled in tools such as Snowsight, Streamlit, Qlik, and SAP BusinessObjects to communicate insights effectively.

Advanced Coding Skills

: Expert-level proficiency in SQL, Python, Shell, and Terraform, with a strong focus on performance, reusability, and maintainability.

Presentation & Communication:

Strong technical and business presentation skills; able to identify and address gaps in data designs and processes with both internal and external

stakeholders.

Pipeline & Orchestration Tools:

Hands-on experience with orchestration tools like Zena and AWS Managed Airflow.

Resilience & Adaptability:

Proven ability to thrive in fast-paced, ambiguous, and high-pressure environments.

Mentorship & Leadership:

A track record of mentoring Data Engineers at all levels, fostering a culture of engineering excellence and continuous improvement.

Customer-Centric Mindset:

Passion for solving real-world problems using data-driven insights to deliver impactful business outcomes.

Collaborative Approach:

Strong interpersonal and communication skills, with the ability to lead teams and influence cross-functional stakeholders.

Domain Knowledge:

Familiarity with insurance industry processes and systems is a strong asset.

AI/ML & GenAI Exposure:

Experience in operationalizing AI/ML & GenAI models is a plus.

Required Certifications (having 2 or more is an asset):

SnowPRO Core,

SnowPRO Advanced Data Engineer (DEA-C01, DEA-C02),

SnowPro Advanced: Architect (ARA-C01), dbt Developer,

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