This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves providing advanced analytical and data engineering support to drive data-informed decision-making and operational efficiency. - Design, develop, and deploy machine learning models for various applications to solve complex business problems. - Build and optimize automated, scalable ETL/ELT pipelines using Python, SQL, and cloud-based tools. - Develop and maintain production ML systems including model deployment and monitoring. - Create interactive dashboards and data visualizations using Tableau, Power BI, or similar platforms. - Conduct data mining, cleaning, and manipulation using SQL and Python. - Translate complex business requirements into technical solutions and analytical frameworks. - Provide technical mentorship on advanced analytics techniques and workflow automation. - Respond to urgent data requests and coordinate collaborative research and analysis projects. Qualifications - At least 5 years of experience in data science, machine learning, or advanced analytics. - Strong proficiency in Python and SQL for data manipulation and analysis. - Experience with ETL/ELT pipeline development and data engineering best practices. - Demonstrated knowledge of data visualization platforms like Tableau and Power BI. - Experience with cloud platforms and modern data infrastructure. - Knowledge of statistical analysis and modeling techniques. - Strong version control and collaboration skills using Git. - Exceptional analytical skills with attention to detail. - Strong communication skills with the ability to present findings to non-technical stakeholders. Benefits - Flexible work hours and remote work options. - Comprehensive medical, dental, and vision plans. - 401(k) plan with company matching. - Generous paid time off and holidays. - Paid parental and family leave. - Short and long-term disability benefits. - Life and accident insurance. - Opportunities for professional development and mentorship.

EōS Fitness is bold, upbeat, and motivating. Not only in our fitness routines, but in our work environment as well. Like our members, our employees know how to rise to a challenge and handle it head on. EōS Fitness' Core Purpose is to create loyal, lifelong fans and exercise practitioners. To achieve this purpose, our Core Values are: Take Personal Responsibility, Be Optimistic & Have Fun, Learn & Grow, Be A Team Player, and Fight Hard To Win. Core Purpose: To create loyal, lifelong fans and exercise practitioners. We’re looking for a Senior Data Engineer experienced in Microsoft Fabric to help architect, build, and scale the next-generation data platform that powers EōS Fitness. This role will lead technical design and engineering across Lakehouse architecture, data pipelines, governance, and analytics enablement. You’ll work closely with Engineering, Sales, Marketing, Operations, Finance, and Member Experience teams to deliver trusted, high‑quality data products that support millions of member interactions across our gyms and digital ecosystem. This role is right for someone who loves building clean, scalable systems, designing high‑quality data products, and optimizing performance across a modern cloud analytics stack. Job Responsibilities Platform & Pipeline Engineering - Architect and maintain Lakehouse solutions in Microsoft Fabric OneLake using Delta Lake and medallion architecture. - Build and automate Data Factory pipelines with parameterization, CI/CD, and strong observability. - Develop and optimize Synapse Spark and SQL workloads for ingestion, transformation, and data modeling. - Partner with BI teams to create performant, governed Power BI semantic models, including Direct Lake. Technical Leadership & Collaboration - Develop and Operate best practices for Fabric, PySpark, SQL, and data modeling. - Work cross‑functionally with Sales, Marketing, Operations, Finance, and Member Services to deliver high‑value data products. - Contribute to engineering standards, documentation, and repeatable frameworks that scale with EōS’s growth. Data Quality, Governance & Reliability - Implement data validation, expectations, lineage, and schema controls to ensure trusted, reliable data. - Support governance frameworks across workspaces, domains, roles, privacy, and security. Job Requirements Required - 10+ years of experience in data engineering or similar technical roles. - 2+ years hands‑on with Microsoft Fabric or equivalent Synapse + ADF + Lakehouse experience. - Strong expertise in SQL and PySpark for large-scale transformations. - Experience building and managing Delta Lake tables, schema evolution, and performance optimization. - Proven experience developing automated ADF/Fabric pipelines in a cloud environment. - Strong understanding of data modeling, dimensional design, and semantic model best practices. - Solid experience with CI/CD (Azure DevOps or GitHub), version control, and environment management. Preferred - Experience with Microsoft Purview or Fabric-native governance. - Familiarity with Direct Lake performance tuning and Power BI optimization. - Knowledge of streaming or event-driven data ingestion. - Background in fitness, membership-based businesses, retail, or multi-location operations. Other Requirements: - Must successfully pass Background Check. - Strong advanced understanding of job requirements and responsibilities. Salary Pay Range $130,000—$150,000 USD Benefits and Perks: - A highly energetic and collaborative team. - A management team that cares about your professional development. - Free membership for you and plus one family member. - Discounted Personal Training, and merchandise – including supplements. - Employee referral program. - Daily Pay offered - access your funds before payday. - Competitive pay plus vacation, holiday, and sick pay.* - Group Health, dental, vision, Supplemental Life, and Employee Assistant Program are offered!* - 401(k) + Company matching!* - Personal education growth options with Sophia Learning. * Based on eligibility of tenure and full-time vs. part-time employment. EōS Fitness is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Employment decisions are based on qualifications, merit, and business needs, without regard to race, color, religion, gender identity, sexual orientation, national origin, age, disability, or any other legally protected status. To view more information on our CCPA policy, click HERE. EEO is The Law - click here for more information Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled EōS Fitness participates in the government eVerify program. Please review the details of this program by clicking here. We endeavor to make this site accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact the Recruiting Help Line at recruitinghelpline@eosfitness.com or by calling 949.309.4182. To check on the status of your application, please visit the Greenhouse Candidate Portal at my.greenhouse.com for updates.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a Senior Data Engineer to own and evolve the commercial data ecosystem that powers insights, performance management, and process optimization at scale. You will architect and deliver advanced data pipelines, analytical data models, front-ends, and Celonis process-mining assets that improve visibility, drive adherence to global processes, and enable data-driven decision-making across Sales, Marketing, Inside Sales, and Commercial Operations. The role emphasizes hands-on engineering and technical leadership, with a deep focus on Celonis process mining, process-adherence mapping, and execution management dashboards. - Work with team members to understand business requirements. - Collaborate with data scientists, business process analysts, and other SMEs to ensure alignment on business objectives and technical requirements. - Maintain a results-oriented mentality and operate with a high sense of urgency. - Demonstrate a proven track record of solving problems, breaking down barriers, and delivering results ahead of schedule. - Design, build, and optimize scalable data pipelines integrating CRM (Salesforce), ERP (SAP), marketing platforms (Marketo), and external datasets. - Model analytics-ready, reusable data layers supporting funnel analytics, forecasting, segmentation, territory management, and sales performance. - Own Celonis data models and event logs; build process-mining analyses, adherence/conformance views, action flows, and operational KPI dashboards. - Implement robust SQL and Python transformations following modular, version-controlled, and testable patterns (e.g., dbt or similar). - Ensure performance, reliability, cost efficiency, and data integrity across pipelines and models (orchestration, monitoring, observability). - Translate business requirements into scalable technical designs; articulate trade-offs and assumptions to technical and non-technical audiences. - Establish data definitions, lineage, and automated validation for commercial reporting; lead root-cause investigations for data quality issues. Qualifications - Bachelor’s or Master’s in Computer Science, Engineering, Information Systems, Mathematics, or related field. - 12+ years in data/analytics/BI engineering with end-to-end pipeline ownership in production. - Expert SQL (advanced joins, window functions, performance tuning) and strong Python (ETL/ELT, APIs, automation). - Hands-on experience with Celonis (or equivalent) including event log design, knowledge models, process-mining analysis, and adherence/conformance. - Experience building executive-ready dashboards in Celonis, Power BI, or Tableau. - Proven ability to translate commercial requirements into scalable, maintainable data solutions and communicate clearly across functions. Company Description Waters Corporation (NYSE:WAT) is a global leader in life sciences and diagnostics, dedicated to accelerating the benefits of pioneering science through analytical technologies, informatics, and service. With a focus on regulated, high-volume testing environments, our innovative portfolio harnesses deep scientific expertise across chemistry, physics, and biology. We collaborate with customers around the world to advance the release of effective, high-quality medicines, ensure the safety of food and water, and drive better patient outcomes by detecting diseases earlier, managing routine infections, and combating antibiotic resistance. Through a shared culture of relentless innovation, our passionate team of ~16,000 colleagues turn scientific challenges into breakthroughs that improve lives worldwide. Diversity and inclusion are fundamental to our core values at Waters Corporation. It benefits our employees, our products, our customers and our community. Waters complies with all applicable federal, state, and local laws. Qualified applicants are considered without regard to sex, race, color, ancestry, national origin, citizenship status, religion, age, marital status (including civil unions), military service, veteran status, pregnancy (including childbirth and related medical conditions), genetic information, sexual orientation, gender identity, legally recognized disability, domestic violence victim status, or any other characteristic protected by law. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. All hiring decisions are based solely on qualifications, merit, and business needs at the time.

• Design, build, and maintain data pipelines and ingestion frameworks on AWS using services such as AWS Glue, S3, and Redshift. • Implement and maintain S3‑based data lakes, including raw, staged, and curated layers, following agreed standards and best practices. • Set up and optimize Amazon Redshift environments, including schema design, distribution and sort key strategies, and performance considerations. • Develop reliable ingestion patterns for file‑based and database sources, including SFTP‑to‑S3 workflows. • Implement secure secrets management using AWS Secrets Manager, ensuring credentials are never stored in code or configuration files. • Build reusable, maintainable transformation logic aligned with agreed modelling and semantic‑layer principles. • Monitor, troubleshoot, and improve pipeline reliability, data quality, and operational stability. • Collaborate with architects, analysts, and client stakeholders to translate requirements into scalable data solutions. • Contribute to defining and enforcing data engineering standards, security practices, and governance patterns. • Support clients during platform adoption, knowledge transfer, and handover.