• Design and build scalable, secure, and cost-effective data solutions in Snowflake • Develop and optimize data pipelines using tools such as dbt, Python, CloverDX, and cloud-native services • Participate in discovery sessions with clients to gather requirements and translate them into solution designs and project plans • Collaborate with engagement managers and account teams to help scope work and provide technical input for Statements of Work (SOWs) • Serve as a Snowflake subject matter expert, guiding best practices in performance tuning, cost optimization, access control, and workload management • Lead modernization and migration initiatives to move clients from legacy systems into Snowflake • Integrate Snowflake with BI tools, governance platforms, and AI/ML frameworks • Contribute to internal accelerators, frameworks, and proofs of concept • Mentor junior engineers and support knowledge sharing across the team

Role Description We are looking for native or fluent language speakers to help train AI systems by reviewing and annotating content in their language (Norwegian). This is a long-term, remote gig. No prior experience is required. On the job training will be provided. What You Will Do - Review content in your native language (e.g., newspaper articles, website screenshots, advertisements) - Draw bounding boxes around specific elements as instructed (e.g., highlight the commercial aspect of an article) - Answer structured questions about the content - Write short summaries when required - Follow clear annotation guidelines to ensure quality and consistency Qualifications - Native or highly fluent speakers of the target language - Students, freelancers, part-time workers, or anyone seeking flexible short-term work - People comfortable following written instructions on a computer Requirements - Strong reading comprehension in your language - Basic computer skills (no technical background needed) - Attention to detail - Ability to follow structured instructions Role Details - Duration: Minimum 6 months (Long-term Project) - Pay Rate: $8 USD / hour - Hours: 30–40 hours/week - Location: Fully remote - Work: Not voice-based — text and image annotation only - No Interview, only assessment: 15–20 minute language skills assessment You will be contracted by Careerflow on behalf of one of our clients.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Data Engineering Expert Type: Contract Compensation: $90–$125/hour Location: Remote Role Responsibilities - Build long-horizon pipeline tasks with deterministic rubrics to grade agent performance against verifiable ground truth. - Develop ETL/ELT pipelines and dbt models to produce specified output tables with incremental logic and defined watermark behavior. - Create Airflow/Dagster DAGs that pass test suites and data quality tests with known pass/fail cases. - Design warehouse schemas matching defined contracts and performance targets tied to measured query-time budgets. - Work independently in long focus sessions to create challenging scenarios for agent evaluation. - Ensure tasks have checkable answers without open-ended essays or subjective judgment calls. Qualifications - Must-Have: BS or MS in CS or related field. - 3+ years in data engineering or analytics engineering. - Expertise in dbt model development, pipeline orchestration (Airflow, Dagster, Prefect), warehouse design (Snowflake, BigQuery, Redshift, Databricks), and data quality and testing. - Comfortable with data engineering artifacts: dbt models, DAGs, schema docs, data contracts, and test suites. - Clear written communication skills to articulate reasoning and encode it into deterministic rubrics. Requirements - Hourly contractor. - Strong contributors are promoted based on task quality and throughput. Application Process - Upload resume. - AI interview based on your resume. - Submit form. For details about the interview process and platform information, please check: Interview Process For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description Join Humana in our mission to put health first by advancing data-driven, connected care across the healthcare ecosystem. As a Principal Data Engineer, you will build and lead an enterprise Integration & Interoperability Center of Excellence (COE)—owning the architecture that connects claims, clinical, pharmacy, and provider workflows at scale, and delivers real-time insights into EMRs at the point of care. If you've worked on platforms at Optum, Change Healthcare, CVS Health, or Elevance Health—this role gives you end-to-end ownership to define the next-generation interoperability layer vs. optimizing a single piece of it. What You'll Own - Build the Integration & Interoperability COE - Stand up and lead a centralized COE for integrations, interoperability, and data exchange - Define enterprise standards across: - FHIR-first and API-first architectures - Event-driven patterns (Kafka, streaming, real-time triggers) - Canonical data models across payer + provider domains - Rationalize and modernize legacy integration patterns (ETL, flat files, point-to-point) - Architect pipelines across: - Claims (837/835), Eligibility (834), Authorizations, Encounters - Clinical data (Epic, Cerner, Athena) - Pharmacy (PBM), labs, ADT feeds, HIE integrations - Enable near real-time ingestion and bidirectional data exchange - Solve for identity, matching, and longitudinal member record creation - Push insights directly into EMRs: - Care gaps (HEDIS) surfaced during visits - Suspected conditions (HCC) at time of documentation - Utilization signals (ED/IP events) via ADT feeds - Build FHIR APIs, SMART on FHIR integrations, and event triggers that actually get used by providers - Build data products that influence: - Star Ratings performance (Medicare Advantage) - HEDIS gap closure at scale - Risk adjustment accuracy and recapture - Move from retrospective reporting → prospective, actionable insights - Design cloud-native platforms leveraging: - AWS / Azure / GCP - Spark, Kafka, Databricks, Delta Lake - Implement data observability (freshness, lineage, quality) - Ensure HIPAA-compliant, secure, governed architectures - Act as a bridge between engineering, clinical, and business teams - Influence roadmap across interoperability, data platforms, and AI - Mentor teams and elevate engineering standards across the org Qualifications - 10+ years in data engineering, with deep healthcare experience - Experience at scale in organizations like: - Optum / Change Healthcare - CVS Health / Elevance Health - Proven track record building integration platforms, not just pipelines - Strong expertise in: - FHIR (R4), HL7v2, CCDA, ADT, APIs - Streaming + batch architectures - Hands-on with: - Python / Scala / Java - Spark, Kafka, SQL - Cloud-native data platforms - Deep understanding of: - Claims, clinical, and pharmacy data models - HEDIS, Star Ratings, Risk Adjustment (HCC) - Experience integrating with EMRs and provider workflows Requirements - You’ve tried to modernize legacy healthcare integrations—and know where they break - You’ve seen the gap between data platforms and provider adoption - You want to build systems that actually change behavior at the point of care - You’re ready to move from incremental improvements → foundational transformation Benefits - Medical, dental and vision benefits - 401(k) retirement savings plan - Time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave) - Short-term and long-term disability - Life insurance - Many other opportunities Additional Information - Location/Work Style: Remote in Frisco/Dallas, TX area - Scheduled Weekly Hours: 40 - Pay Range: $172,200 - $236,900 per year - This job is eligible for a bonus incentive plan based upon company and/or individual performance.