Data Engineer

Summary

Join Wave as a Data Engineer and build the tools and infrastructure supporting Data Products, Insights & Innovation teams, and the business. You will design, build, and deploy components of a modern data stack, including a Hudi data lake and various pipelines. Collaborate with cross-functional teams, ensuring reliable data delivery for analytics, machine learning, and GenAI services. Resolve incidents, optimize pipelines, and improve data workflows. This role requires 3+ years of data engineering experience, AWS cloud proficiency, strong coding skills (Python, SQL, dbt), and experience with data lake development. Wave offers flexible work arrangements, including remote options, and invests in employee growth and well-being through various benefits.

Requirements

• Bring 3+ years of experience in building data pipelines and managing a secure, modern data stack. This includes CDC streaming ingestion using tools like Debezium into a Hudi data lake that supports AI/ML workloads and a curated Redshift data warehouse
• At least 3 years of experience working with AWS cloud infrastructure, including Kafka (MSK), Spark / AWS Glue, and infrastructure as code (IaC) using Terraform
• Write and review high-quality, maintainable code that enhances the reliability and scalability of our data platform. We use Python, SQL, and dbt extensively, and you should be comfortable leveraging third-party frameworks to accelerate development
• Prior experience building data lakes on S3 using Apache Hudi with Parquet, Avro, JSON, and CSV file formats
• Build and manage multi-stage workflows using serverless Lambdas and AWS Step Functions to automate and orchestrate data processing pipelines
• Familiarity with data governance practices, including data quality, lineage, and privacy, as well as experience using cataloging tools to enhance discoverability and compliance
• Experience developing and deploying data pipeline solutions using CI/CD best practices to ensure reliability and scalability
• Working knowledge of tools such as Stitch and Segment CDP for integrating diverse data sources into a cohesive ecosystem

Responsibilities

• Design, build, and deploy components of a modern data stack, including CDC ingestion (using Debezium), a centralized Hudi data lake, and a variety of batch, incremental and stream-based pipelines
• Build and manage a fault tolerant data platform that scales economically, while balancing innovation with operational stability by maintaining legacy Python ELT scripts and accelerating the transition to dbt models in Redshift
• Collaborate within a cross-functional team in planning and rolling out data infrastructure and processing pipelines that serve workloads across analytics, machine learning and GenAI services
• Help different teams across Wave succeed by ensuring that their data, analytics, and AI insights are reliably delivered
• Independently identify opportunities to optimize pipelines and improve data workflows under tight deadlines
• Respond to PagerDuty alerts and proactively implement monitoring solutions to minimize future incidents, ensuring high availability and reliability of data systems
• Provide technical assistance, listen to and communicate with people to help answer their concerns
• Assess existing systems, optimize data accessibility, and provide innovative solutions to help internal teams surface actionable insights that enhance external customer satisfaction

Preferred Qualifications

Knowledge and practical experience with Athena, Redshift, or Sagemaker Feature Store to support analytical and machine learning workflows

Benefits

• Work From Where You Work Best: We will always have a welcoming, energizing, and world-class office (in Toronto) with a space for you. Or, if you’re more comfortable working from home, the choice is yours
• You will stretch yourself and you will grow at Wave. You will also be supported on this journey with diverse learning experiences, educational allowances, mentorship, and so much more
• We make a serious investment in your health & wellness. When we think about benefits we think about body, mind, & soul and we take this stuff very seriously
• Fair compensation, all the office perks you’d want, and the various goodies you’d expect from a growing tech company