Role Description Please find the below requirement and let me know your interest? - 100% Remote - W2 Role - More than 10 Years of Data Modeling Experience with experience on ERWIN tool. - MUST HAVE HAD EXPERIENCE WITH MULTIPLE FINANCIAL/BANKING CLIENTS. - Experience developing conceptual, logical, and physical data models for databases, data warehouses, and analytics systems. - Experience implementing and maintaining data modeling standards, best practices, and governance policies. Qualifications - More than 10 Years of Data Modeling Experience - Experience with ERWIN tool - Experience with multiple financial/banking clients Requirements - Experience developing conceptual, logical, and physical data models - Experience implementing and maintaining data modeling standards - Experience with best practices and governance policies Company Description Thanks, Jagdish | Manager - IT Staffing T (443)-489-4433 | Jagdish@polarits.com 6095 Marshalee Dr, Suite 250, Elkridge, MD 21075 Note: If you have received this message in error, please notify us immediately by reply e-mail so that we may correct our internal records. Please then delete the original message (including any attachments) in its entirety. Thank you.

Role Description Oxford Client is building a new Planning System and needs a Data Engineer to assist. Qualifications - Strong experience in data engineering and pipeline development in enterprise environments. - Advanced SQL skills, including complex joins, window functions, and performance optimization. - Experience with cloud data platforms, data lakes, and curated analytical layers. - Proficiency in Python or similar scripting languages for data transformation and automation. - Hands-on experience integrating data from SAP or other ERP systems. - Solid understanding of data modeling, including dimensional and time series data. Requirements - Experience implementing data quality checks, validations, and monitoring. - Understanding of data governance, access controls, and regulatory or audit considerations. - Familiarity with supply chain and planning concepts, including demand forecasting, supply planning, inventory management, and capacity planning. - Understanding of planning KPIs such as forecast accuracy and bias, service levels, inventory turns, and cost tradeoffs. - Experience supporting planning, optimization, or decision support systems is highly desirable. Benefits - Exposure to Advanced Planning / Supply Chain Planning platforms (e.g., Kinaxis, OMP, SAP IBP, Blue Yonder). - Experience supporting scenario modeling, simulation, or optimization engines. - Experience in global manufacturing or high mix, low volume environments.

Role Description We are seeking a Senior Data Engineer who is a self-starter to work in a diverse and fast-paced environment as part of our Capital Markets Data Engineering team. This individual contributor role is responsible for designing and developing data solutions that are strategic to the business and built on the latest technologies and patterns. This is a global role that requires partnering with the broader JLLT team at the country, regional, and global levels by utilizing in-depth knowledge of data, infrastructure, technologies, and data engineering experience. Responsibilities - Technical Development - Design and implement robust, scalable data pipelines using Databricks, Apache Spark, and Delta Lake as well as BigQuery. - Design and implement efficient data pipeline frameworks, ensuring the smooth flow of data from various sources to data lakes, data warehouses, and analytical platforms. - Troubleshoot and resolve issues related to data processing, data quality, and data pipeline performance. - Document data infrastructure, data pipelines, and ETL processes, ensuring knowledge transfer and smooth handovers. - Create automated tests and integrate them into testing frameworks. - Platform Engineering - Configure and optimize Databricks workspaces, clusters, and job scheduling. - Work in a Multi-cloud environment including Azure, GCP, and AWS. - Implement security best practices including access controls, encryption, and audit logging. - Build integrations with market data vendors, trading systems, and risk management platforms. - Establish monitoring and performance tuning for data pipeline health and efficiency. - Collaboration & Mentorship - Collaborate with cross-functional teams to understand data requirements, identify potential data sources, and define data ingestion. - Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions that meet their needs. Qualifications - Bachelor's degree in Computer Science, Data Engineering, or a related field (Master's degree preferred). - Minimum 5+ years of experience in data engineering or full-stack development, with a focus on cloud-based environments. Requirements - Advanced expertise in managing big data technologies (Python, SQL, PySpark, Spark) with a proven track record of working on large-scale data projects. - Strong Databricks experience. - Advanced database/backend testing with the ability to write complex SQL queries for data validation and integrity. - Strong experience in designing and implementing data pipelines, ETL processes, and workflow automation. - Experience with data warehousing concepts, dimensional modeling, data governance best practices, and cloud-based data warehousing platforms (e.g., Google BigQuery, Snowflake). - Experience with cloud platforms such as Microsoft Azure or Google Cloud Platform (GCP). - Experience working in DevOps model. - Experience with Unit, Functional, Integration, User Acceptance, System, and Security testing of data pipelines. - Proficiency in object-oriented programming and software design patterns. - Familiarity with cutting-edge AI technologies and demonstrated ability to rapidly learn and adapt to emerging concepts and frameworks. Core Competencies - Strong problem-solving skills and ability to analyze complex data processing issues. - Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams. - Attention to detail and commitment to delivering high-quality, reliable data solutions. - Ability to adapt to evolving technologies and work effectively in a fast-paced, dynamic environment. Location Remote – Jalisco, MEX Benefits - If this job description resonates with you, we encourage you to apply even if you don’t meet all of the requirements. - We’re interested in getting to know you and what you bring to the table!

Role Description NBME is looking for a Data Engineer to join a highly skilled and growing team of data engineers and BI developers. This team successfully launched and enhances a data product on AWS for medical doctors. In this role, you will use your data engineering and problem-solving skills to deliver meaningful insights to internal staff and external customers. The Data Engineer will help modernize, expand, and optimize NBME's data platform by building data lakes, complex data integration pipelines, and scalable data solutions that support analytics, AI/ML, and business decision-making. This role will apply AI-assisted engineering practices to improve development efficiency and share best practices for AI-assisted engineering across the IT organization. While this role can be designated as remote, you are offered the flexibility to select if you prefer to work primarily remotely, hybrid, or onsite. We're open to considering candidates within 50 miles of our office location in Philadelphia, PA. Please note that onsite interviews and onboarding at our Philadelphia office may be required for this role. At NBME, we continue to innovate and improve how we fulfill the evolving needs of the healthcare community. This commitment starts and ends with the people at NBME. By recruiting and empowering talented individuals from various disciplines and backgrounds, which includes professionals with diverse life experiences, abilities, and perspectives, NBME can take a well-informed, robust approach to advancing medical education and assessment for years to come. Responsibilities - Code, test, deploy, orchestrate, monitor, document, and troubleshoot cloud-based data engineering processes, feature stores, and vector databases in accordance with best practices and security standards throughout the development lifecycle. - Partner closely with data scientists, AI researchers, data and enterprise architects, and business stakeholders to identify, extract, clean, and format structured and unstructured data for AI/ML model training, fine-tuning, and feature extraction. - Lead evaluation, research, and experimentation efforts with batch and streaming data technologies, LLM data preparation frameworks, and MLOps tools to keep pace with industry innovation. - Act as a technical lead to showcase the capabilities of emerging AI and data technologies, enabling the widespread adoption of modern data techniques across the organization. - Significantly contribute to the definition and refinement of processes and procedures for the data engineering practice. - Educate and develop ETL developers on data engineering cloud-based initiatives to enable transition to data engineer and practice. - Assure the integrity and accuracy of the corporate data, with particular attention to data security. - Responsible for ensuring high data quality for Data Services, Analytics, and Master Data Management. - Help coordinate technical solutions, taking responsibility for designs, development, testing, and delivery of solutions. - Build automated, scalable, test-driven data pipelines. - Utilize software development practices such as version control via Git, CI/CD, and release management to enhance existing CI/CD pipelines in AWS. - Collaborate with Data Engineers, DevOps engineers, and architects on improvement opportunities for DataOps tools and frameworks. Qualifications - Bachelor's Degree - At least 7 years of experience in application development (Internship experience does not apply) - At least 4 years of experience in big data technologies - At least 4 years' experience with cloud computing using AWS - 4+ years of experience in application development including Python, SQL, Scala, or Java - 4+ years' experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, MySQL etc.) - 4+ year experience working on real-time data and streaming applications - 4+ years of experience with NoSQL implementation (Mongo, Cassandra) - 4+ years of data warehousing experience (Redshift) - 6+ years of experience with UNIX/Linux including basic commands and shell scripting - 7+ years of experience with Agile engineering practices - 7+ years of experience with SQL optimization - 4+ years of experience with PySpark - 3+ year of experience with process orchestration including AirFlow, KubeFlow, AWS step functions, or Luigi Preferred Qualifications - Proven experience implementing Generative AI, LLM data preparation pipelines, and Vector Databases (e.g., Pinecone, Milvus, pgvector). - Strong experience building and maintaining Feature Stores for machine learning models. - Experience building highly scalable, secure, and production-ready APIs and Data-as-a-Service (DaaS) platforms. - AWS Certified Data Engineer or AWS Certified Machine Learning – Specialty certifications. - 3+ year of experience with Machine Learning. - Experience with building a Data-as-a-service platform. - Experience with building APIs. Benefits - Healthcare, Dental, Prescription, and Vision plans - 401(k) w/match - Tuition Reimbursement Plan - Commuter Benefit: Public Transit or Parking options - Remote Friendly Workplace Compensation The compensation we are offering for this position is at $127,337- $160,000/year. Please note that the offered rate for this position typically aligns with the minimum to midrange of this grade, but it can vary based on the successful candidate's qualifications and experience, department budget, and an internal equity review. Company Description NBME is a not-for-profit organization that specializes in the creation of assessments and learning tools for physicians and health professionals. Our mission is to advance assessment of these professionals to achieve optimal care for all, supporting the development of a highly effective, diverse, and compassionate health care workforce. Founded in 1915, NBME develops and manages the United States Medical Licensing Examination® with the Federation of State Medical Boards. We offer a comprehensive portfolio of assessment products for every stage of the medical school journey and provide assessment services to various health profession organizations. We are dedicated to advancing innovative assessment approaches through research, collaboration, and contributions to the medical education and assessment communities.