AWS Data Platform Engineering Lead – AWS Data Services
Summary
Leads AWS data platform engineering, designing scalable cloud-native data pipelines and frameworks while mentoring teams and driving innovation in AWS services for enterprise-wide data initiatives.
Location: Toronto: Hybrid 2 days a week in office Role Overview We are seeking a Senior Data Engineer with strong AWS expertise to lead the design, development, and evolution of scalable, high-performance data platforms. This role is responsible for building cloud-native data engineering frameworks, optimizing complex data pipelines, and evaluating emerging AWS services to drive innovation and efficiency. 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. |