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# Data Engineer

- **Company:** ABSENCESOFT LLC
- **Location:** Denver, CO, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Microsoft Azure, BigQuery, Cloud Computing, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Distributed Computing Environment, Python (Programming Language), Cloud Services, SQL Databases, Data Streaming, Workflow Management Systems, Pinecone, Feature Store, Large Language Models, Snowflake, Apache Spark, Usage Tracking, Data Lakes, Apache Flink, Weaviate, Machine Learning Operations, FAISS, Terraform, Data Pipelines, Docker, Amazon Redshift, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_0a8d5fbdf0131f07d6b6475821c6c514

## About the Role

* 5+ years of experience as a data engineer building large-scale, production-grade data pipelines.
 * Strong command of SQL, Python, and distributed data processing frameworks (Spark, Flink, Beam).
 * Hands-on experience with ETL/ELT tools and orchestration systems (Airflow, dbt, Prefect, Dagster).
 * Familiarity with cloud-native data platforms (e.g., Snowflake, BigQuery, Redshift, Databricks).
 * Experience supporting ML/AI workloads and collaborating closely with model development teams.
 * Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate) and embeddings management.
 * Understanding of data privacy, access control, and compliance in regulated environments.
 * Proficiency in modern DevOps tooling for data infrastructure (Docker, Terraform, CI/CD pipelines).
 * Ability to work autonomously and drive projects in a startup-paced, enterprise-focused environment.

Nice To Have

 * Cloud Providers: AWS (Redshift, S3, Lambda), Azure (Data Lake, Synapse), GCP (BigQuery, Cloud Functions)
 * Workflow Tools: dbt, Airflow, Dagster, Prefect

## Description

We're seeking a Data Engineer to design and manage the data pipelines, platforms, and tools that power intelligent AI applications. You will work closely with data scientists, AI software engineers, and product teams to ensure our ML and LLM workloads are backed by scalable, secure, and high-performance data infrastructure. This is a hands-on, high-impact role where reliability and flexibility of data architecture is paramount.

We're looking for engineers who care about data as infrastructure-building durable, elegant, and secure systems that power intelligent decision-making at scale., * Design, build, and maintain data pipelines for structured, unstructured, and semi-structured data sources.

 * Develop and optimize data models, ETL processes, and batch/streaming data infrastructure.
 * Partner with data scientists to support training, evaluation, and deployment of traditional ML and LLM models.
 * Implement scalable architectures for embeddings, vector databases, and retrieval pipelines.
 * Enable real-time and offline analytics workflows through best-in-class data engineering practices.
 * Ensure data quality, lineage, observability, and governance across all data products.
 * Contribute to the design of feature stores and MLOps platforms for continuous learning and model updates.
 * Collaborate on Responsible AI workflows to ensure compliant data usage and access controls for sensitive information.
 * Continuously evaluate new tools and technologies for improving performance, reliability, and data agility.
 * Participate in a highly compliant environment while assisting to maintain company controls and security within your job role.
 * Other duties as assigned.