Data Engineer - AWS

Tiger Analytics, LLC; Vancouver; On-site; CAD 80,000 - 110,000; Full time

Job summary

An innovative consulting firm is seeking an experienced AWS Data Engineer to join their dynamic team. This role involves designing and maintaining scalable data pipelines on AWS, collaborating with cross-functional teams, and optimizing data workflows for performance and reliability. The ideal candidate will have extensive experience with AWS services, Databricks, and Apache Spark, contributing to impactful analytics and business intelligence initiatives. If you are passionate about data engineering and eager to work in a fast-paced environment, this is the perfect opportunity for you.

Qualifications

• 8+ years of experience in building and deploying data pipelines.
• Strong proficiency in AWS services and data processing tools.

Responsibilities

• Design and deploy data pipelines on AWS using various services.
• Collaborate with teams to understand data requirements and deliver solutions.

Skills

AWS Services

Databricks

SQL

Apache Spark

Data Engineering

Problem-solving

Communication Skills

Tools

Git

Apache Airflow

Job description

Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Engineering, Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

As an AWS Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines on AWS cloud infrastructure. You will work closely with cross-functional teams to support data analytics, machine learning, and business intelligence initiatives. The ideal candidate will have strong experience with AWS services, Databricks, and Snowflake.

Key Responsibilities:

• Design, develop, and deploy end-to-end data pipelines on AWS cloud infrastructure using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
• Implement data processing and transformation workflows using Databricks, Apache Spark, and SQL to support analytics and reporting requirements.
• Build and maintain orchestration workflows using Apache Airflow to automate data pipeline execution, scheduling, and monitoring.
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver scalable data solutions.
• Optimize data pipelines for performance, reliability, and cost-effectiveness, leveraging AWS best practices and cloud-native technologies.

• 8+ years of experience building and deploying large-scale data processing pipelines in a production environment.
• Hands-on experience in designing and building data pipelines
• Strong proficiency in AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, etc.
• Strong experience with Databricks, Pyspark for data processing and analytics.
• Solid understanding of data modeling, database design principles, and SQL and Spark SQL.
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Excellent communication skills and the ability to collaborate effectively with cross-functional teams.
• Strong problem-solving skills and attention to detail.

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.