Data Engineer
Listed on 2026-06-18
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IT/Tech
Data Engineering, Data Science Manager, Cloud Computing: Infrastructure & Operations
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This range is provided by Absence Soft. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range$/yr - $/yr
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.
Who We Are
Absence Soft is elevating the leave and accommodations experience and is looking to hire amazing people like you! We create user-friendly, secure, and compliant technology that empowers employers to bring humanity, certainty and efficiency to the leave and accommodations experience. Made by HR Professionals for HR Professionals, we're proud of where we've been and excited about where we're headed. We value creative, innovative people who are passionate about their work and who believe there is always a better way.
Leading With Our Core Values
Make a Difference.
We are inspired to make an impact through our hard work, talent and passion. We push ourselves each day to better serve our teams, our clients, and our community.
Team First.
We are driven by team spirit not by self-interest. We value collaboration and approach our work with humility and a desire to win together.
Own it.
If we say it, we mean it. We follow through on our commitments, step up to deliver, and grow from our successes and failures.
Everyone Matters.
No matter your background or experience, everyone's voice holds value here.
What You’ll Do
- 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.
What’ll Set You Up for Success
Required Skills:
- 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, Big Query, 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 Dev Ops 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 (Big Query, Cloud Functions)
- Workflow Tools: dbt, Airflow,…
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