AWS DATA ENGINNER

Apptoza Inc.; Toronto; Vor Ort; CAD 120.000 - 190.000; Vollzeit

Zusammenfassung

Apptoza Inc. seeks a senior technical leader to define data strategy and establish best practices across engineering, analytics and business teams. You will lead cloud-native data pipelines on AWS, drive scalable batch and streaming architectures, and mentor mid-level data engineers.

You will champion data quality, observability, and cost optimization while shaping enterprise-wide data strategy and architectural governance.

Qualifikationen

• 10+ years of experience in Data Engineering or Software Engineering.
• 4-5 years of dedicated hands-on experience with AWS.
• Proven experience designing and implementing large-scale, production-grade data platforms.
• Expertise with AWS data services, including S3, Glue, Redshift, EMR, Lambda, Step Functions, Kinesis, MSK.
• Strong programming skills in Python, Scala, or Java.
• Deep experience with ETL/ELT frameworks and data pipeline orchestration tools, including Airflow and AWS-native orchestration services.
• Strong understanding of data modeling, distributed systems, and performance tuning.
• Experience with CI/CD practices and Infrastructure as Code tools such as Terraform, AWS CDK, or CloudFormation.
• Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Aufgaben

• Lead the design, development, and enhancement of cloud-native data engineering frameworks on AWS.
• Architect, build, and optimize end-to-end batch and streaming data pipelines for scalability, reliability, and performance.
• Drive experimentation and adoption of new and emerging AWS services to improve platform capabilities and operational efficiency.
• Establish data engineering standards, patterns, and best practices for data ingestion, transformation, and storage.
• Partner with analytics and product teams to support reporting, analytics, and business objectives.
• Own data quality, monitoring, observability, and cost optimization strategies across the data platform.
• Provide technical leadership and mentorship to mid-level data engineers.
• Participate in architectural reviews and contribute to enterprise-wide data strategy and decision-making.

Kenntnisse

Python

Scala

Java

Data modeling

Distributed systems

Mentorship

Communication

Tools

Airflow

Terraform

AWS CDK

CloudFormation

Amazon S3

AWS Glue

Amazon Redshift

Amazon EMR

AWS Lambda

AWS Step Functions

Amazon Kinesis

Amazon MSK

Jobbeschreibung

As a senior technical leader, you will collaborate with architecture, analytics, and business teams to define long-term data strategy, establish engineering best practices, and support enterprise-wide data initiatives.

Key Responsibilities

Lead the design, development, and enhancement of cloud-native data engineering frameworks on AWS.

Architect, build, and optimize end-to-end batch and streaming data pipelines for scalability, reliability, and performance.

Drive experimentation and adoption of new and emerging AWS services to improve platform capabilities and operational efficiency.

Establish data engineering standards, patterns, and best practices for data ingestion, transformation, and storage.

Partner with analytics and product teams to support reporting, analytics, and business objectives.

Own data quality, monitoring, observability, and cost optimization strategies across the data platform.

Provide technical leadership and mentorship to mid-level data engineers.

Participate in architectural reviews and contribute to enterprise-wide data strategy and decision-making.

Required Qualifications

10+ years of experience in Data Engineering or Software Engineering.

4-5 years of dedicated hands-on experience with AWS.

Proven experience designing and implementing large-scale, production-grade data platforms.

Expertise with AWS data services, including:

• Amazon S3
• AWS Glue
• Amazon Redshift
• Amazon EMR
• AWS Lambda
• AWS Step Functions
• Amazon Kinesis
• Amazon MSK

Strong programming skills in Python, Scala, or Java.

Deep experience with ETL/ELT frameworks and data pipeline orchestration tools, including Airflow and AWS-native orchestration services.

Strong understanding of data modeling, distributed systems, and performance tuning.

Experience with CI/CD practices and Infrastructure as Code tools such as Terraform, AWS CDK, or CloudFormation.

Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders.

Preferred Qualifications

Experience evaluating and implementing new AWS services through proof-of-concept initiatives.

Exposure to real-time streaming data architectures.

Knowledge of data governance, security, and compliance within cloud environments.

Experience supporting analytics, business intelligence, or machine learning platforms.

Experience working within Agile frameworks.

AWS certifications such as:

• AWS Certified Data Analytics - Specialty
• AWS Certified Solutions Architect

Technical Leadership Expectations

Serve as a senior technical leader for AWS data engineering initiatives.

Influence data platform architecture, engineering standards, and best practices.

Guide teams in building scalable, reliable, and cost-effective data solutions.

Promote innovation through the evaluation and adoption of emerging AWS capabilities.

Main Improvements

Improved structure and readability.

Eliminated repetitive language while preserving all original requirements.

Clarified leadership expectations and AWS-specific responsibilities.

Standardized qualification and technology sections for a more market-ready JD.