Data Engineer building Azure ETL/ELT pipelines and governed data architecture for Manulife’s financial services business. Supporting scalable analytics, automation, and operational excellence.
About the role
- Senior Data Engineer building AWS/GCP data infrastructure for Ready’s broadband monitoring and BEAD programs. Developing reliable pipelines, data quality systems, and AI-enabled workflows.
Responsibilities
- Partner with product and engineering teams to understand requirements and translate them into technical architecture
- Evaluate and recommend data tools, frameworks, and infrastructure choices
- Contribute to roadmap discussions and build-vs-buy decisions
- Design, implement, and maintain scalable AWS data infrastructure
- Own data lake and warehouse architecture, including partitioning, storage optimization, and data lifecycle management
- Build and maintain production-grade Apache Airflow DAGs for ingestion, transformation, and export workflows
- Ensure observability through monitoring, alerting, and incident resolution
- Build and maintain dbt pipelines with data quality checks and structured data modeling
- Design and maintain database schemas for multi-state, multi-tenant program data
- Write and optimize SQL queries across PostgreSQL, Redshift, and Athena
- Develop reusable data models, utilities, and shared Python packages
- Design infrastructure for large-scale time-series and event-based data
- Implement ingestion, storage, and retrieval patterns for high-frequency temporal datasets
- Work with vector databases for AI-powered features and semantic search
- Integrate LLM workflows into ELT pipelines using AWS Bedrock, LangChain, and related frameworks
- Build production AI-assisted data comparison, validation, and enrichment pipelines
- Work with MLflow and deploy production-level ML pipelines
- Monitor AI/ML tooling developments and bring relevant innovations to the team
- Design automated data QA systems for dataset quality, completeness, and consistency
- Implement cleansing and reconciliation routines for multi-source ingestion
- Proactively monitor pipelines and resolve issues before downstream impact
- Mentor junior and mid-level data engineers through code reviews, pair programming, and architectural guidance
- Establish standards for code quality, testing, and documentation
- Foster ownership, curiosity, and continuous improvement on the data team
Requirements
- 5+ years of data engineering experience with ownership and operational support of production systems end-to-end
- Ability to evaluate technical trade-offs and make pragmatic architecture decisions balancing cost and performance
- Strong proficiency in SQL, including PostgreSQL and Athena/Presto
- Strong proficiency in Python and production-quality coding
- Deep hands-on experience with AWS data services: S3, Athena, RDS, ECS, Lambda, IAM, and CloudWatch
- Production experience with Apache Airflow or similar orchestration tools
- Experience with large-scale time-series, event-based, or streaming data systems
- Experience with version control using GitHub, Subversion, GitLab, or Mercurial
- Familiarity with vector databases and LLM integration patterns such as LangChain and AWS Bedrock
- Experience building data quality frameworks or automated validation systems
- Demonstrated ability to mentor engineers and contribute to team culture
- Excellent communication skills for explaining complex infrastructure decisions to non-engineers
- Comfortable working with ambiguity and making first-principles decisions
- Comfortable working across multiple time zones
- Experience managing data for SaaS platforms is a plus
- Experience with large-scale spatiotemporal data pipelines, including PostGIS, spatial indexing, and tiling, is a plus
Benefits
- Competitive (and ever expanding) benefits for employees and dependents
- Opportunities to learn and grow – all things startups
- Work from anywhere you want, as long as you can get great internet
- Optional, encouraged retreats 2–3 times per year
- Opportunity to shape the benefits program
- Meaningful equity upside
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