Role Description We are looking for a Data Engineer to support a strategic data platform migration, moving tables, views, and stored procedures from Amazon Redshift to Databricks. You will build and support Databricks pipelines and jobs, work with AWS services including S3, Glue, and Athena, and apply data governance practices including data lineage, cataloging, and role-based access controls throughout the migration. This is a 5–6 month project engagement. What You Will Do - Migrate tables, views, and stored procedures from Amazon Redshift to Databricks. - Build and support Databricks pipelines and jobs. - Work with AWS services, including Amazon S3, AWS Glue, and Amazon Athena. - Support data migration activities within a modern data lake architecture. - Apply data governance and data management practices throughout the migration. - Collaborate with project stakeholders to support migration activities. Qualifications - 3–5 years of experience as a Data Engineer. - Hands-on experience with Databricks. - Experience with Amazon Redshift. - Strong SQL skills. - Experience with AWS services, including Amazon S3, AWS Glue, and Amazon Athena. - Experience building and supporting Databricks pipelines and jobs. - Understanding of data lake architectures. - Familiarity with data governance and data management practices, including data lineage, data catalogs, and role-based access controls (RBAC). - Upper-intermediate English level. Nice to Haves - Experience with Databricks Lakebridge transpiling capabilities. Benefits - Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget. - Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews. - Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm. - Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands. - Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized. - Well-being & support: access local well-being programs and people-focused support tailored to your location.

Role Description The Sr. Quality Data & Analytics Specialist is responsible for transforming data into meaningful insights that support product quality, patient safety, regulatory compliance, and operational excellence within global Getinge. This role combines expertise in statistical analysis, data analytics, artificial intelligence (AI), and data integration to support businesses with pro-active signal detection, reducing patient risk. This position is ideal for an analytical professional who enjoys solving complex problems, leveraging modern analytics and artificial intelligence (AI) tools, and helping business partners make informed decisions using data. Job Responsibilities and Essential Duties - Statistical Analysis & Trending: - Act as a Subject Matter Expert in Statistical methods. - Support legal manufacturers with selection of appropriate statistical methodologies. - Data Analytics & Business Intelligence: - Develop and implement dashboards, scorecards, and visualizations. - Continuously improve insights of dashboards and visualizations. - Present complex analytical findings to both technical and non-technical audiences. - Support management reviews and quality performance reporting activities. - Artificial Intelligence & Automation: - Identify opportunities to leverage AI and automation. - Evaluate emerging AI technologies and recommend practical business applications. - Support implementation, testing, validation, and monitoring of AI-enabled solutions. - Help establish best practices for responsible and effective use of AI. - Data Management & Integration: - Work with data from multiple sources. - Identify opportunities to improve data quality, accessibility, and usability. - Collaborate with IT and stakeholders to improve data connectivity. - Assist in developing data models and reporting structures. - Cross-Functional Collaboration: - Partner with Legal Manufacturers and functional stakeholders. - Support quality and regulatory initiatives through data-driven analyses. - Participate in continuous improvement projects. - Provide training and guidance to business partners on data interpretation. Qualifications - Bachelor’s or Master’s Degree in a relevant field (e.g., statistics, data science, biostatistics, mathematics). - A minimum of 5 years relevant experience in data analytics, data science, medical device quality, healthcare analytics, or statistical techniques. - Solid knowledge and application of Descriptive statistics, Statistical trend analysis, Hypothesis testing, Risk-based monitoring, Data visualization techniques. - Ability to interpret complex datasets and communicate statistics concepts clearly. - Understanding of Generative AI, Large Language Models (LLMs), Machine Learning fundamentals. - Curiosity for emerging technologies and analytical methods. - Ability to communicate effectively and work collaboratively in a cross-functional environment. - Experience with applications such as Power BI, Tableau, SQL, Python, R, Microsoft Fabric, Databricks, Snowflake, Azure analytics tools, Microsoft Copilot or similar AI platforms. Requirements - Problem solver & critical thinker with attention to detail. - Ability to identify practical applications of AI that improve processes and efficiency. Benefits - Health, Dental, and Vision insurance benefits. - 401k plan with company match. - Paid Time Off. - Wellness initiative & Health Assistance Resources. - Life Insurance. - Short and Long Term Disability Benefits. - Health and Dependent Care Flexible Spending Accounts. - Commuter Benefits. - Parental and Caregiver Leave. - Tuition Reimbursement. Company Description With a firm belief that every person and community should have access to the best possible care, Getinge provides hospitals and life science institutions with products and solutions aiming to improve clinical results and optimize workflows. Getinge employs over 12,000 people worldwide and the products are sold in more than 135 countries.

Role Description As a Soccer Data Correspondent you will collect information about individual players, squads and relevant events that take place during the game, like player substitutions, cards and scorers. - Ensure updating squads of the teams and competitions you are responsible for within the agreed deadlines. - Collaborate remotely with our in-office data editors team. - Confirm the accuracy of our data by regularly reviewing additional sources such as official team pages and social media. - Acquire in-depth knowledge of the squads assigned to you in order to ensure accurate data. Qualifications - Basic English knowledge. - Excellent communication skills. - Country specific knowledge of geography (national/international), time zone, local top teams, players and the local competitions. - Attention to detail and commitment to accuracy. - Experience in data analysis and/or data collection would be an advantage. Benefits - The perfect freelance opportunity in the sports industry. - Thorough training to master the usage of our tools. - An environment full of sport enthusiasts.

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, Delta Lake, and related cloud-native data engineering tools • Develop and support batch and streaming data workflows, including ingestion, transformation, validation, and publishing of curated data products • Write, optimize, and maintain Python, PySpark, and SQL code for data processing, orchestration, and performance tuning • Work with large-scale datasets using Databricks, Spark, Delta Lake, Unity Catalog, and cloud storage services • Troubleshoot and resolve data pipeline failures, performance issues, data quality issues, and workflow bottlenecks • Translate business and technical requirements into data engineering designs, processing scripts, and job orchestration workflows • Perform data validation, quality checks, code reviews, and issue resolution to support accurate and reliable data products • Collaborate with cross-functional teams including solution architects, data scientists, analysts, DevOps engineers, and client stakeholders • Communicate technical concepts, delivery impacts, and data engineering considerations to technical and non-technical audiences • Document pipelines, datasets, data models, workflows, and engineering decisions to support maintainability, transparency, and reuse • Follow data governance, security, lineage, and compliance standards within the Databricks platform