Senior Data Engineer

Job Title: Senior Data Engineer

Department: Enterprise Services

Reports To: Erick Olson

Location: Remote

Orijin:

Orijin is on a mission to prepare every justice-impacted individual for sustainable employment. We partner with facilities and employers to empower justice-impacted individuals with the necessary educational tools to rewrite their life stories. We are the original ed tech company that provides secure tablet computers connected to our robust cloud-based learning and communications platform to solve some of the most consequential challenges correctional facilities face across the U.S. Our approach has proven to exceed the technological needs of correctional facilities, reduce recruitment and retention costs for employers, and lead our learners to sustainable employment.

Orijin is a Public Benefit Corporation (PBC) and certified B-Corporation, with a business model that never charges incarcerated individuals or their friends and families for its technology or services. Orijin products and services are currently deployed in over 150+ facilities across 18 states and growing. You can learn more about Orijin’s work by visiting: https://orijin.works.

The Opportunity

As a Senior Data Engineer at Orijin, you will be a technical leader responsible for building, scaling, and modernizing the company’s data platform. Your primary focus will be on data modeling, pipelines, architecture, reliability, and performance, ensuring that data is trusted, timely, and production-ready.

As a member of the Enterprise Services team, you will partner closely with data analysts, engineers and product managers to shape how data is modeled and used. You will bring an analytical mindset to pipeline design and enable high-quality insights across the organization. You will ensure company-wide confidence in data quality and enable data-enabled differentiating products and services.

Data Platform & Architecture Leadership

-Design and evolve Orijin’s data architecture to support scalability, reliability, and near–real-time use cases.

-Define standards for data modeling, orchestration, versioning, and deployment.

-Lead efforts around data governance, security, lineage, and compliance in partnership with stakeholders.

-Drive the transition toward modern data stack best practices (event-driven ingestion, streaming where appropriate, modular pipelines, ETL, and data storage).

Data Engineering & Pipeline Ownership

-Own the design, build, and maintenance of production-grade data pipelines across batch and streaming workloads.

Buildsystems that support:

*Monitoring, alerting, and observability for data pipelines.

*Backfills re-runs, and safe rollbacks when failures or data issues occur.

*High data quality and reliability through automated checks and validation.

-Optimize pipelines for performance, cost efficiency, and scalability.

-Lead the move toward near real-time data processing where it delivers business value.

Tooling & Infrastructure

-Architect and maintain data systems using tools such as:

*AWS (S3, RDS, Redshift, Lambda, DMS, Glue etc.)

*Data orchestration and ETL tools like Airflow, Airbyte and dbt and related processing frameworks

-Improve CI/CD for data workflows, including testing, deployment, and environment management.

-Evaluate and introduce new tooling for orchestration, monitoring, and data quality as the platform matures.

ML & AI Enablement

-Design build, and operate production-grade data and feature pipelines that support machine learning and AI-driven product features, including training, evaluation, inference, monitoring, and safe rollout to downstream systems.

-Support vectorization and embedding workflows, including generation, storage, refresh, and backfill of embeddings.

-Partner with team stakeholders to translate model requirements into scalable, reliable data systems.

-Contribute to early experimentation and prototyping of ML-powered features where deep data platform context is required.

Analytics Enablement & Collaboration

-Partner with analysts and product teams to ensure pipelines and data models support meaningful analysis and reporting.

-Provide architectural input on metrics design, data models, and semantic layers.

-Enable self-service analytics by ensuring clean, well-documented, and accessible datasets.

-Basic proficiency in data visualization platforms with demonstrated ability to build and maintain data dashboards

-Contribute to exploratory analysis or metric definition when deeper engineering context is required.

Efficiency & Reliability Focus

-Continuously improve:

*Query performance

*Storage and compute costs

*Pipeline runtime and failure rates

-Lead incident response for data outages and quality issues, including root-cause analysis and permanent fixes.

-Establish SLAs and reliability standards for critical data assets.

Qualifications

-Bachelor’s or advanced degree in Computer Science, Engineering, Data Science, or equivalent work experience.

-Expertise in the areas of data engineering, platform engineering, or backend engineering roles.

-Proven experience designing and operating large-scale data pipelines and data platforms in production enviroments.

-Strong proficiency in Python and SQL for data engineering workflows.

-Hands-on experience with AWS data tools like Redshift, Lambda and Glue or equivalents; experience with data orchestration and ETL tools like Airflow, Airbyte and dbt in production enviroments.

-Experience implementing monitoring, alerting, and data quality frameworks.

-Familarity with streaming or near–real-time systems (e.g., Kafka, Kinesis, or similar) is a plus.

-Hands on experience with PostgreSQL databases and NoSQL style databases like MongoDB, DynamoDB, etc.

-Experience supporting machine learning or AI workflows (e.g., feature engineering, embedding pipelines, model inputs/outputs, embeddings, vector databases).

-Strong collaboration and communication skills - able to translate business and analytical needs into robust technical systems.

-Experience with data governance, security, and compliance in regulated or sensitive-data environments.

$120,000 - $127,000 a year

Salary and Benefits

● Orijin offers competitive compensation commensurate and a generous 100% employer-paid benefits package for you and your dependents.

● Occasional Travel as needed and the ability to work EST.

Equal Opportunity Employer :

Orijin is an Equal Opportunity Employer and firmly believes in creating a workplace that respects and values diversity of cultural, ethnic, and experiential backgrounds. We encourage all qualified applicants to apply. As an organization committed to the successful reentry of justice-involved persons, we strongly encourage candidates who share the life experiences of the citizens we serve to apply

Disclaimer: The above statements are intended to describe the general nature and level of work being performed by the individual assigned to this position. They are not intended to be an exhaustive list of all duties, responsibilities, and skills required. Job duties may change or new duties assigned at any time with or without notice