WE’RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further.

Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions. We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients.  If this sounds exciting to you, let’s chat!

Data Architect

You own the data spine of the platform: the canonical event envelope, the multi-tenant transactional store, the read-side projections that power every console view and API response, and the AI/ML data infrastructure that makes the system intelligent rather than just instrumented. This is not a specialist role. We are hiring one person who has done all three surfaces at production depth and can hold the trade-offs simultaneously. The data volume is significant, the schema evolution problem is hard, the tenant isolation requirements are unforgiving, and the AI workloads sit on top of all of it. If any of those three surfaces feel uninteresting, this isn't the role. You'll work shoulder-to-shoulder with the Solution Architect on the canonical data model and with the Senior Developer on implementation. You write the migration playbooks, the upcaster chains, the projection rebuild procedures, and the runbooks that let us sleep at night. You will sit in our headquarters in Dallas, TX on a hybrid schedule. The team is in office on Tuesdays, Wednesdays and Thursdays. 

What experience should you have:

• 10+ years of data engineering, data platform, or database architecture experience, with at least 3 owning the architecture, not just the implementation.
• Production experience with event-sourced systems. You have personally implemented or evolved an event envelope, dealt with the upcaster chain problem, and lived with the consequences of an early schema decision.
• Deep Postgres expertise: schema design, indexing, query plan analysis, RLS. Not "I've used Postgres" but "I know what I'd do differently from the last team."
• Experience with streaming platforms: Kafka, Redpanda, Pulsar, or Kinesis. You understand the difference between a topic, a partition, a consumer group, and a saga, and you've designed for all of them.
• Production analytical data infrastructure experience: warehouse design (Snowflake, BigQuery, Databricks, ClickHouse) or modern OLAP patterns. You can take an event log and produce a queryable shape that analysts and AI systems can actually use.
• Hands-on AI/ML data infrastructure experience: vector databases (pgvector, Pinecone, Weaviate, Qdrant), embedding pipelines, retrieval patterns. You have shipped a RAG system that worked and you know why most of them don't.
• Strong SQL, strong enough to be the person other engineers go to.

Nice to have

• Drizzle, Prisma, or another modern TypeScript ORM at production depth.
• Workflow engine experience (Temporal, Cadence, Airflow) and the data implications of long-running processes.
• Background in feature stores, ML pipelines, or model evaluation infrastructure.
• Semantic layer experience: dbt, Cube, or Malloy.
• Compliance experience: SOC 2, HIPAA, GDPR, data residency. The audit story is part of the data story.
• Open-source work or public writing on data architecture.

What you’ll be doing in this role:

• The canonical event envelope and schema evolution strategy: how events are versioned, how upcasters chain, how projections rebuild, and how we add fields without breaking history. You write the rules and enforce them in code review.
• The transactional data layer: Postgres schema design, tenant isolation via row-level security, indexing strategy, query patterns, and migration discipline. Every table in a data plane carries a tenant_id and a policy. You make sure of that.
• The read-side architecture: projection design, materialized views, semantic layer for downstream analytics and AI consumption. You decide how we move from event log to queryable shape and how that shape stays cheap to maintain.
• The AI/ML data infrastructure: vector stores, embedding pipelines, retrieval-augmented generation patterns, feature stores where applicable, and the lineage that lets us trust what comes back.
• Data governance: lineage, retention, deletion (right-to-be-forgotten in a multi-tenant event-sourced system is a real problem and you'll solve it), and the audit story for every piece of customer data we touch.
• The operational playbook: projection rebuilds, replay procedures, schema migrations on hot data, vector index maintenance, capacity planning. If the data layer goes sideways at 2am, your runbook is what saves the on-call engineer

Our total rewards program is designed for your protection, peace of mind, and overall well-being. In addition to our outstanding basics, we offer a net-zero cost medical option, company contributions to your HSA, fertility support, fully-paid parental leave, a monthly stipend for your lifestyle spending account, and much more.

Apply today or check out all our opportunities!

#LI-Hybrid

Applicants must be currently authorized to work in the United States on a full-time basis. The company does not anticipate providing sponsorship for employment visa status (e.g., H-1B, TN, etc.) for this individual position.

Hi, we're Oscar. We're hiring a Data Analytics Associate to join our Service Operations Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You may at times be called upon to speak to prepared analysis both internally and externally.

You will report into the Manager, Data Analytics.

Work Location: This is a remote position, open to candidates who reside in: Dallas, Texas. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 2+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 2+ years experience in SQL, with the ability to filter, aggregate, and build CTEs
• 2+ years in building robust data models
• 1+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools

Bonus points:

• Experience using Python or R
• 2+ years experience in healthcare or insurance industry
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience
• Prior experience in Member Relations or Customer Success environments.
• Building data models in dbt
• Building reports in Looker Studio Pro
• Git workflows

We are searching for a Senior Data Analyst, Workforce Strategy to join the Operations Excellence team, who would be based in Dallas, TX. In this role, you will forecast, allocate, and optimize all operations headcount to align resource plans and schedules to hiring and vendor engagement strategies. You will be at the forefront of our staffing and vendor management strategy, working closely with cross-functional teams to gather and analyze data, identify trends, and develop plans that support our operational goals. This role requires strategic orchestration, analyzing workforce needs, and driving momentum under a fast-paced, ever-changing environment.

In this role, you will:

• Partner with Operations, Strategy, Recruiting, and Finance leaders to forecast and align headcount needs against organizational strategy and roadmap
• Build sophisticated financial and operational models that connect business drivers to staffing requirements, recruiting / vendor management plans, and budget implications
• Build intuitive dashboards, metrics, and reports that highlight staffing utilization, labor productivity constraints, and capacity gaps
• Partner with senior Operations and Finance leaders to develop scenarios balancing service levels, cost optimization, and growth objectives
• Apply probabilistic modeling, Python-based simulation modeling, and artificial intelligence to simulate cost & efficiency trade-offs and resource optimization
• Lead monthly headcount data analysis and vendor management strategy reviews to synthesize headcount performance inputs from multiple stakeholders into cohesive strategic recommendations
• Analyze large, disparate datasets to uncover statistical trends in labor productivity and attrition
• Monitor workforce KPIs and identify program gaps or execution issues that impact profitability and scalability
• Improving data integrity and automating manual reporting workflows to increase functional efficiency

Required Qualifications: 

• 5+ years of experience in data science, management consulting, investment banking, engineering operations, FP&A, or strategic operations, ideally in a fast-scaling tech environment
• Bachelor’s degree and / or work experience in a quantitative field (e.g. Operations Research, Business Analytics, Economics, Math, Statistics, Finance)
• Exceptional Excel / Gsheets financial modeling skills, SQL, Python and statistical modeling skills and working with business intelligence tools (e.g., Mode, Tableau)
• Experience building/maintaining data pipelines and DBT models
• Strategic mindset with ability to balance detailed analysis with big-picture thinking
• Track record of multi-functional leadership and excellent stakeholder management to drive rapid, effective execution across the organization
• Strong executive presence with demonstrated ability to communicate complex analyses clearly to senior stakeholders
• Superior attention to detail
• Ownership mentality to drive issues and tasks to completion, with a strong bias for action

The base salary range for this position is $104,000 - $150,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-KM2

 #Mid-Senior