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Data Tech Lead/Architect (AWS)

  • Canada

Full-time

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Job details

Job type
Full-time
Posting language
English
Posted

Original job description

We are looking for an experienced AWS Data Tech Lead/Architect to design and deliver scalable, secure, and cost-effective data solutions on AWS. The role requires hands-on work.

Engagement: long-term, full-time.

Location: ON/QC (ideally), Canada. !!! Readiness for business trips to Montreal in the next 3 months.

Responsibilities
  • Design AWS data platforms, data lakes, warehouses, and ETL/ELT pipelines.
  • Define data architecture, data models, integration patterns, and governance standards.
  • Work with AWS services such as S3, Glue, Redshift, Athena, Lambda, EMR, Kinesis, and Lake Formation.
  • Lead data migration and modernization projects.
  • Ensure data security, quality, performance, and cost optimization.
  • Work closely with data engineers, developers, architects, and business teams.
  • Provide technical guidance and review architecture/designs.
Required Skills and Experience:
  • 5+ years of experience in data architecture, data engineering, or related roles.
  • 3+ years of hands-on AWS experience designing and implementing data solutions.
  • Strong knowledge of AWS data and analytics services.
  • Experience designing data lakes, data warehouses, and lakehouse solutions.
  • Strong understanding of ETL/ELT, data pipelines, and distributed data processing.
  • Proficiency in SQL and experience with Python, Java, or Scala.
  • Strong knowledge of data modeling, dimensional modeling, and database architecture.
  • Experience with technologies such as Spark, Kafka, Airflow, dbt, or similar platforms.
  • Experience with cloud security, IAM, encryption, networking, and data governance.
  • Understanding of CI/CD, Infrastructure as Code, and DevOps practices.
  • Experience with data migration and modernization projects.
  • Strong analytical, problem-solving, communication, and stakeholder-management skills.
Working conditions:
  • 16 days of paid time off.
  • Official public holidays.
  • Participation in company events.
  • Health insurance.
  • Engaging projects with opportunities for career growth.
  • Certifications, Claude/other tools needed.
  • Corporate events, team-building activities.
  • Gifts and recognition from the company.
  • A friendly, open, and supportive team culture without excessive bureaucracy.
More about this job

Responsibilities

Design and deliver scalable, secure, cost-effective AWS data platforms, architectures, models, and ETL/ELT pipelines, including data lakes and warehouses. Lead migration and modernization work, optimize security, quality, performance, and cost, and provide technical guidance while collaborating with engineering, architecture, and business teams.

Requirements

Requires at least five years in data architecture, data engineering, or a related role, including at least three years of hands-on AWS experience designing and implementing data solutions. Candidates should have strong AWS analytics, data modeling, distributed processing, programming, cloud security, governance, CI/CD, and Infrastructure as Code knowledge, along with migration experience and strong communication and problem-solving skills.

Skills

  • AWS Data Architecture
  • Data Engineering
  • Data Lakes
  • Data Warehousing
  • Lakehouse Solutions
  • ETL/ELT
  • SQL
  • Python
  • Java
  • Scala
  • Data Modeling
  • Spark
  • Kafka
  • Airflow
  • Cloud Security
  • Infrastructure as Code

Benefits

  • Paid Time Off
  • Public Holidays
  • Company Events
  • Health Insurance
  • Career Growth Opportunities
  • Certifications
  • Team-Building Activities
  • Gifts and Recognition
  • Supportive Team Culture

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Software
  • Management & Leadership

Keywords

  • AWS
  • Amazon S3
  • AWS Glue
  • Amazon Redshift
  • Amazon Athena
  • AWS Lambda
  • Amazon EMR
  • Amazon Kinesis
  • AWS Lake Formation
  • Data Architecture
  • Data Engineering
  • Data Lakes
  • Data Warehouses
  • Lakehouse
  • ETL/ELT
  • Data Pipelines
  • Distributed Data Processing
  • SQL
  • Python
  • Java
  • Scala
  • Data Modeling
  • Dimensional Modeling
  • Spark
  • Kafka
  • Airflow
  • dbt
  • IAM
  • Encryption
  • Data Governance

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