Remote Data Jobs • Airflow

The Manager of Data Engineering will lead a team of talented data engineers, overseeing the design, development, and maintenance of our foundational data capabilities, architecture, and infrastructure. This role is crucial for building robust, scalable data pipelines and platforms that support advanced analytics and business intelligence, ensuring our data systems are efficient, reliable, and aligned with organizational goals.

The Senior Data Analyst will take ownership of business intelligence and analytics initiatives. This person will play a critical part in shaping the data culture of our company by defining core business metrics to enabling stakeholder insights through visualizations and deep-dive analyses. This person will work with stakeholders across the company, as well as the executive leadership team, to deliver highly visible analyses.

This is a hands-on technical leadership role to shape the future of Moonpay's data platform. As a Senior Data Engineer on the Data Platform team, you will design, build, and optimize the core infrastructure and services that empower developers and data users. You will also mentor other engineers on the team and improve the existing data platform codebase.

As a Senior Analytics Engineer at Bungie, you will be responsible for building and extending the data warehouse for our analytics platform, with a primary focus on Marathon. You will design and develop scalable data models that bridge the gap between raw data and business insights. You will work closely with analysts, data scientists, and game developers to understand their analytical needs and transform complex gaming data into accessible, reliable datasets.

Shape Finaloop's data infrastructure at the forefront of Fintech and AI. You'll join a high-impact R&D team in a fast-paced startup environment, building scalable pipelines and robust data systems that empower eCommerce businesses to make smarter decisions.

As a Senior BI and Analytics Engineer at BetterHelp, you’ll deliver scalable, trustworthy, and impactful data solutions that empower teams working on insurance-related initiatives. You will deliver dashboards and ad-hoc analyses with a focus on payer data and health plan performance and ensure data quality and compliance at every stage of the pipeline. You will partner with data and ML engineers and work with a modern data stack: Airflow, FiveTran, Snowflake, dbt, and Looker.

As VP, Data & Technology you will architect this spine, build and inspire a world-class organization (Data Engineering, Data Science / Gen AI, Software Engineering), and partner with Growth, Finance, Actuary, Value Delivery, and Clinical leaders to turn insight into outsized P&L impact. Strategic technology leadership to translate complex analytics into clear, actionable narratives for business and clinical stakeholders.

Build data infrastructure to enable more timely and personalized engagement with individuals living with SMI at scale. This allows the team of peers, social workers, and nurse practitioners to plan appropriate care and focus on critical tasks rather than manually searching for information across silos in the healthcare system. This is a unique opportunity to found and define the data engineering team, stack and architecture, with a high caliber product and data team that is growing quickly.

Spark is looking for a Senior Data Engineer to join our data team. As a Senior Data Engineer, you'll focus on building scalable backend systems, implementing modern data tools, and improving the data pipelines that serve as the foundation of our data ecosystem. You'll work closely with product, engineering, and the broader data team to ensure our data infrastructure meets both current needs and future growth.

Lead and grow our data engineering team, overseeing the implementation, integration, and maintenance of client data into SmarterDx products and services. Accountable for team performance including feature delivery, quality, operational excellence, hiring, retention, professional growth, and well-being. Guide the design and implementation of robust ETL pipelines and drive continuous improvement in data processes.