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Remote Senior Data Engineer

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Über

Orijin is on a mission to prepare every justice-impacted individual for sustainable employment.
We are 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. (
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.
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. Job Requirements 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 t he transition toward
modern data stack best practices
(event-driven ingestion and streaming where appropriate).
Data Engineering & Pipeline Ownership
Own the
design, build, and maintenance of production-grade data pipelines
across batch and streaming workloads.
Build systems 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
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
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.
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.
Fully remote with option to work in person in NYC office.
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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
  • United States

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  • English
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