Position Overview Join FUJIFILM Biotechnologies to power analytics at scale. We’re seeking a Senior Data Engineer with deep expertise in Alteryx and Tableau to design, build, and operate scalable data pipelines and modern analytics platforms. You’ll shape engineering standards, elevate platform reliability and performance, and deliver secure, audit‑ready solutions that accelerate decision‑making across a regulated enterprise. Company Overview The work we do at FUJIFILM Biotechnologies has never been more important—and we are looking for talented candidates to join us. We are growing our locations, our capabilities, and our teams, and looking for passionate, mission-driven people like you who want to make a real difference in people’s lives. Join FUJIFILM Biotechnologies and help make the next vaccine, cure, or gene therapy in partnership with some of the most innovative biopharma companies across the globe. We are proud to cultivate a culture that will fuel your passion, energy, and drive - what we call Genki. Fujifilm is globally headquartered in Tokyo with over 70,000 employees across four key business segments of healthcare, electronics, business innovation, and imaging. We are guided and united by our Group Purpose of “giving our world more smiles.” Visit: https://www.fujifilm.com/us/en/about/region/careers Job Description What you’ll do - Engineer pipelines that deliver impact: Design, build, and maintain high‑performance batch/streaming pipelines (SQL, dbt and/or Alteryx) for data products, analytics, and AI. - Own Alteryx at scale: Configure, administer, and optimize Alteryx Server/Cloud (environments, schedules, credentials, governance, packaging/promotions, upgrades). - Elevate Tableau performance: Engineer/administer Tableau Server/Cloud (sites/projects, permissions, extracts, schedules, LCM, performance tuning, version upgrades). - Run platforms like a pro: Implement monitoring/alerting, SLOs, capacity planning; troubleshoot incidents; drive root‑cause elimination and reliability improvements. - Raise data quality: Implement quality checks, lineage, and observability; define standards for naming, modeling, documentation; contribute to catalog/metadata. - Build security/compliance in: Align with Cybersecurity, data privacy, and where applicable GxP/21 CFR Part 11; execute changes under ITIL/PMO governance. - Partner to deliver: Translate business needs into technical designs; balance delivery velocity with platform health and best practices. - Be the escalation point: Provide L2/L3 support, guide service desk, maintain runbooks/knowledge articles, participate in on‑call rotations as needed. - Optimize for performance and cost: Tune queries/extracts; right‑size compute/storage; drive license hygiene and cost efficiency. - Standardize and improve: Establish engineering standards, SOPs/WIs, templates, peer reviews; evaluate and introduce targeted innovations. Minimum requirements - Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field; or an equivalent combination of education and experience. - 8+ years of related experience with a Bachelor’s; or 6+ years with a Master’s; or PhD with 3+ years; or equivalent experience. - Within the above, 5+ years in data engineering and/or analytics platform engineering, including 3+ years hands‑on administering and operating Alteryx and Tableau in enterprise settings. - Strong SQL and dimensional/relational data modeling; experience with data transformation/integration tools (e.g., Alteryx, dbt, Azure Data Factory/Talend). Preferred requirements - Certifications: Alteryx Designer (Core/Advanced) and/or Server Admin; Tableau Desktop Specialist/Certified Professional, Tableau Server/Cloud Admin; ITIL Foundation v3/v4; cloud certifications (Azure/AWS/GCP) are a plus. - Hands‑on with Snowflake (highly considered); Python for automation; CI/CD (Git, DevOps pipelines); infrastructure‑as‑code basics. - Experience in biotech/life sciences or other regulated industries; familiarity with data privacy and, where applicable, GxP/CSV/CSA and 21 CFR Part 11. What’s in it for you - Impact at enterprise scale: Your engineering will power analytics and AI across functions. - Technical leadership: Set standards, mentor peers, and influence platform roadmaps. - Modern stack + growth: Advance your skills across Alteryx/Tableau, dbt/SQL, cloud data services, and automation. EEO Information Fujifilm is committed to providing equal opportunities in hiring, promotion and advancement, compensation, benefits, and training regardless of nationality, age, gender, sexual orientation or gender identity, race, ethnicity, religion, political creed, ideology, national, or social origin, disability, veteran status, etc. ADA Information If you require reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please direct your inquiries to our HR Department (fdbglobaltalent@fujifilm.com).

Overview Opening available for Senior Software Engineer - Healthcare Data Lake and MDM at Cotiviti, Inc. in South Jordan, UT. Responsibilities Build and manage large-scale data systems. Design, develop, and optimize our data-intensive applications and data lakehouse. Work with cloud services, modern messaging systems, and a variety of database technologies. Engineer solutions that handle complex entity mastering and entity resolution for healthcare provider and member data. Ensure systems are designed and operated in a HIPAA-compliant manner. Secure PHI/PII and leverage industry standards like HL7 and FHIR. Design, build, and maintain scalable data pipelines and event-driven architecture. Manage our Big Data solutions and evolve our Lakehouse platform for analytics and machine learning. Develop and optimize complex data models, queries, and ETL processes for both NoSQL and relational databases. Utilize AWS for large-scale, cost-effective data storage and implement data-lifecycle policies. Collaborate with data scientists, analysts, and other engineers to build robust, high-performance applications. Ensure data integrity, system reliability, and performance efficiency across all platforms. Troubleshoot and resolve complex technical issues in distributed data systems. Mentor junior engineers and contribute to setting technical standards and best practices. Qualifications Bachelor’s degree or foreign equivalent degree in Computer Science, Software Engineering, or related. Five (5) years of progressive experience in software or data engineering in Python with a focus on back-end systems. Employer will accept a Master’s degree or foreign equivalent degree in Computer Science, Software Engineering, or related and three (3) years of experience as stated in lieu of a Bachelor’s degree and five (5) years of experience. Work experience to include: Three (3) years of experience with Master Data Management (MDM); Three (3) years of experience with AWS; Three (3) years of experience building and managing serverless functions with AWS Lambda; Three (3) years of experience implementing message queues for decoupled systems; Three (3) years of experience with [each of] at least two of the following storage, retrieval and management services: Amazon S3, Document DB and/or MongoDB; Three (3) years of experience with managing and scaling Kafka clusters for real-time data streaming with Amazon MSK; Three (3) years of database experience with relational databases Oracle and SQL Server; Three (3) years of experience with schema design, indexing, aggregation pipelines and performance tuning in MongoDB; Three (3) years of experience with Messaging Systems including Rabbit MQ and Kafka; Three (3) years of experience with design, building or maintaining lakehouse data architecture; and Three (3) years of experience with Big data principles; Three (3) years of experience with Healthcare data interoperability standards through data engineering (i.e., FHIR, HL7, EHR, EDI and 837); and Two (2) years of experience with Spark and Hadoop ecosystems. Any and all experience may be gained concurrently. Telecommuting available anywhere in the U.S. Company headquarters located at 10701 South River Front Pkwy, Suite 200, South Jordan, UT 84095. Base compensation ranges from At least $158,787. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. #LI-DNI #immigration

At Ensono, our Purpose is to be a relentless ally, disrupting the status quo and unleashing our clients to Do Great Things! We enable our clients to achieve key business outcomes that reshape how our world runs. As an expert technology adviser and managed service provider with cross-platform certifications, Ensono empowers our clients to keep up with continuous change and embrace innovation. We can Do Great Things because we have great Associates. The Ensono Core Values unify our diverse talents and are woven into how we do business. We achieve our purpose by living five core values: Honesty, Reliability, Collaboration, Curiosity, and Passion! At Ensono, we are evolving into a software-first Managed Services Provider—a place where AI, automation, and human expertise work together to deliver 10x productivity for our clients. Our Envision Operating System is the backbone of this transformation, orchestrating operations across mainframe, distributed, and cloud environments. Data Engineer (Operational Data & AI Enablement) The Data Engineer plays a pivotal role in Ensono’s evolution toward predictive, zero‑touch managed services. This is not a traditional analytics or back‑office data role. As an operational data and AI enablement engineer, you will design and build production‑grade data pipelines and platforms that power predictive services, anomaly detection, and intelligent automation. From ServiceNow tickets to mainframe and cloud telemetry, you’ll turn raw, noisy operational signals into high‑quality, AI/ML‑ready datasets that enable real‑time insights and proactive operations. The work you do directly impacts uptime, cost optimization, and Ensono’s ability to move from manual, reactive support to a predictive, automated model. We are looking for engineers who don’t just architect pipelines but get things done—builders who deliver working solutions, iterate quickly, and collaborate closely with data scientists, ML engineers, and operations teams to ensure models don’t just run in notebooks but meaningfully change how work gets done in production. If you want to be part of the team rewiring managed services for the AI era, this is your role. What You Will Do Data Pipeline Development Build, optimize, and maintain ELT/ETL pipelines that ingest, clean, and organize operational data from ServiceNow, mainframe environments, distributed systems, and cloud platforms. ServiceNow Data Integration Develop robust extraction, transformation, and ingestion patterns for ServiceNow operational data (incidents, alerts, changes, requests), ensuring it is reliable, well‑modeled, and ready for AI/ML use cases. Data Infrastructure & Architecture Design scalable data models, storage frameworks, and integration layers in Snowflake and related modern data platforms, with an emphasis on performance, reliability, and operational relevance. Data Quality & Governance Implement data quality standards, monitoring, validation, and lineage to ensure pipelines produce clean, trustworthy, and auditable datasets. Collaboration with AI/ML Teams Partner with Data Scientists, ML Engineers, and MLOps to deliver and maintain production‑grade feature pipelines, training datasets, and inference‑ready data, supporting predictive models, anomaly detection, and intelligent runbooks. ML Deployment Enablement Support ML production workflows by enabling model registration, versioning, and lifecycle management within Snowflake, working alongside ML and MLOps teams (model development itself is not the primary responsibility of this role). Snowflake AI & LLM Integration Integrate Snowflake AI components, including Cortex LLMs, into data workflows for use cases such as enrichment, summarization, and operational intelligence. Automation & Optimization Identify opportunities to streamline data workflows, reduce manual intervention, and lower operational costs while improving reliability and scalability. Cross‑Functional Enablement Work with Finance, Procurement, Cloud Operations, Mainframe Operations, and Service Operations teams to ensure data products align with high‑value business outcomes. We want all new Associates to succeed in their roles at Ensono. That's why we've outlined the job requirements below. To be considered for this role, it's important that you meet all Required Qualifications. - Strong SQL skills and solid data modeling fundamentals - Expertise in ELT/ETL pipeline development and orchestration - Python (required) plus experience with at least one of Java, Scala, or C++ - Hands‑on experience with Snowflake or equivalent cloud data warehouse platforms - Minimum of 2 years Snowflake experience required - Proven experience extracting, transforming, and operationalizing data from ServiceNow and/or other enterprise operational systems (e.g., monitoring platforms, ITSM, finance, or HR systems such as Workday or Concur) - Familiarity with observability tooling and distributed data systems - Knowledge of enterprise data governance, compliance, and data lineage practices - Experience supporting AI/ML feature pipelines in production environments - 7+ years' experience is required Mindset & Values - Get Stuff Done – Biased toward execution and results over prolonged design cycles - Business Impact Driven – You build pipelines that directly improve uptime, cost efficiency, and operational predictability - Collaborative Partner – Comfortable working at the intersection of Operations, AI/ML, and business stakeholders - Continuous Learner – Actively explores new tools and techniques to accelerate delivery and improve outcomes Success Looks Like - Reliable pipelines that pull ServiceNow data into Snowflake to support real‑time incident prediction - Faster transitions of AI/ML proof‑of‑concepts into production‑ready data pipelines - Demonstrated cost savings through automated workload optimization and capacity forecasting - Predictive services that scale seamlessly across mainframe, distributed, and cloud environments This Role Is a Strong Fit If You… - Have built data pipelines for operational or event‑driven systems, not just analytics or reporting - Enjoy working close to reliability, uptime, and cost outcomes - Have supported ML systems in production by delivering dependable, high‑quality data - Prefer shipping working solutions over perfect architectures - Are comfortable owning pipelines end‑to‑end, from source systems through production consumption Why Ensono? Ensono is a place where we unleash Associates to Do Great Things – for our clients and for your career. This could mean achieving a professional goal, collaborating with your team on an innovative idea, learning a new skill, reaching a wellness milestone, or engaging in your community through volunteer programs. Whatever it means to you, we want Ensono to be the place where you can do great things. We value flexibility and work-life balance. Positions that are not required to be onsite to support a client may offer the ability to work remotely or hybrid at an Ensono office location. - Unlimited Paid Days Off - Three health plan options - 401k with company match - Eligibility for dental, vision, short and long-term disability, life and AD&D coverage, and flexible spending accounts - Family Forming Benefit including fertility coverage and adoption/surrogacy reimbursement - Paid childbearing and paternal leave - Education Reimbursement, Student Loan Assistance or 529 College Funding - Sabbatical leave - Wellness program - Flexible work schedule As of the date of this posting, a good faith estimate of the current pay scale for this role is $114,000 to $148,000 annually based on a full-time schedule. Please note that placement in the range may vary based on numerous factors including but not limited to skills, experience, internal equity, and business needs. In addition to base salary, other compensation programs, depending on eligibility, include an annual bonus plan based on company and individual performance, and an equity grant under our Associate Equity Appreciation Program. Ensono is an Equal Opportunity/Affirmative Action employer. We are committed to providing equal employment to our Associates and building a diverse and inclusive workforce. All qualified applicants will be considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or other legally protected basis, in accordance with applicable law. Pay transparency nondiscrimination statement/posting OFCCP’s pay transparency policy can be found on OFCCP’s website. If you need accommodation at any point during the application or interview process, please let your recruiter know or email USTalentAcquisition@ensono.com.

The Customer Intelligence Engineer builds scalable intelligence workflows that help Seeq’s Customer Success organization act earlier, smarter, and more strategically. This role sits within Customer Success and operates at the intersection of product usage analytics, customer health modeling, workflow automation, and applied AI. The mission is to transform raw customer data—usage, engagement, and contract signals—into actionable insights delivered to the right people at the right time. This is an early-career, high-potential role ideal for an engineering graduate or former process engineer pivoting into analytics and software.   Key Duties & Responsibilities: Build Customer Intelligence Workflows - Design and deploy account-level Slack summaries for CSMs and leadership. - Translate product usage and contract data into operational signals. - Build or extend data pipelines in partnership with Analytics Engineering. - Develop Python-based automation to operationalize insights at scale. Improve Health & Renewal Predictability - Contribute to Seeq’s customer health scoring framework. - Develop usage-to-renewal correlation models. - Identify leading indicators of risk, expansion, and adoption. - Iterate based on measurable predictive lift and CS feedback. Apply AI and Modern Tooling - Leverage AI-first coding workflows to accelerate development. - Build lightweight LLM-driven synthesis workflows where valuable. - Help elevate development practices across Customer Success. Partner Cross-Functionally - Work directly with CSMs to understand real decision workflows. - Collaborate with Analytics Engineers on modeling and data structure. - Feed product insights back into Engineering through internal dogfooding.