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Data Engineer II

Job ID: 25-12339
Pay rate range - $65/hr. to $70/hr. on
Onsite

Must Have
Data pipelines
ETL
SQL

Degree/Experience:
  • Bachelors Degree in Data Engineering, or any related
  • 3-6 years in Data Engineering building and maintaining production data pipelines
  • Experience in SQL and ETL
We're looking for a Data Engineer to join AI for a focused engagement to lead the migration of critical data infrastructure that powers sustainability metrics, carbon footprint calculations, and Climate Pledge Friendly badging across Devices.

Responsibilities:
As a Data Engineer on the Sustain.AI team, you will be working with business-critical sustainability data pipelines.
You will be responsible for migrating production ETL jobs from legacy data platforms to modern AWS infrastructure, ensuring zero disruption to operations that drive corporate carbon footprinting, quarterly business reviews, and customer-facing sustainability communications.

You will establish the technical foundation for our data infrastructure by setting up Redshift clusters, AWS Glue, and workflow orchestration platforms in new AWS accounts.
You will translate existing data workflows into scalable AWS pipelines, implementing robust validation to ensure data consistency and quality throughout the migration.

You will work across multiple critical data domains including sales data, active device telemetry, transportation carbon emissions, energy consumption metrics, sustainability badging workflows, and executive reporting dashboards.
You will partner with Science team members who own carbon calculation methodologies and program teams who depend on these pipelines for daily operations, understanding their requirements and ensuring migrated solutions support their analytical and operational needs.

You will coordinate with upstream data owners to secure access permissions, collaborate with platform teams to troubleshoot integration issues, and communicate migration progress and risks to stakeholders across the organization.
Clear communication will be essential as you navigate dependencies across multiple teams and ensure alignment on migration timelines and success criteria.

You will be responsible for comprehensive documentation of the new architecture, including data lineage, dependencies, monitoring strategies, and operational runbooks.
This documentation will enable the AI team to maintain and evolve the infrastructure after your engagement completes.
You will implement data quality checks and alerting to proactively identify issues before they impact downstream consumers.

Required Skills & Experience:
3-6 years building and maintaining production data pipelines in complex enterprise environments
Strong SQL skills for writing complex transformations, optimizing query performance, and troubleshooting data quality issues across large datasets
Hands-on experience with AWS data services including Redshift, S3, Glue, and IAM for data access management
Deep understanding of ETL best practices including data validation, error handling, idempotency, and lineage tracking
Experience with Python or Spark for implementing data transformation logic
Strong analytical skills and ability to work with large, complex datasets spanning multiple source systems
Excellent communication and stakeholder management skills, with ability to coordinate across multiple technical teams and translate technical concepts for non-technical audiences
Ability to partner directly with technical stakeholders to understand requirements and deliver solutions that meet operational needs
Proven track record managing data migrations or large-scale infrastructure transitions with minimal business disruption

Preferred Qualifications:
Experience with workflow orchestration platforms
QuickSight experience for dashboard development
Background in large-scale data migrations
Familiarity with sustainability data, carbon accounting, or environmental metrics
Experience setting up monitoring and alerting for production data pipelines
 
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