Role Description This role is a hands-on technical leadership position focused on the strategic design, ongoing operation, and continuous improvement of enterprise-wide data platforms. You will own key data engineering technologies and serve as the central point of contact for various partner organizations. Emphasis is placed on ensuring platforms are secure, scalable, cost-effective, and adhere to enterprise standards. Key Responsibilities: - Oversee the complete data engineering platform lifecycle. - Establish and maintain platform standards and best practices. - Drive platform roadmaps and the adoption of modern data patterns. - Collaborate with cybersecurity, cloud infrastructure, and DevOps teams. - Provide technical guidance and enforce dbt standards for data engineers. Qualifications - Strong experience managing enterprise data platforms. - Hands-on experience with DevOps and CI/CD. - Excellent communication and cross-functional collaboration abilities. - Experience in large enterprise or regulated environments is preferred, particularly supporting federated development teams utilizing shared data platforms. Requirements - Snowflake (advanced) - Informatica (advanced) - dbt (advanced) - AWS (advanced) - CI/CD (advanced) Benefits - Contract Type: W2 - Duration: 12+ Months - Location: Remote - Pay Range: $60-$65/hr. on W2

Role Description Delivering complete, accurate, and trusted data from multiple source systems into Azure-based data platforms. This role supports scalable data pipelines and analytics solutions that enable data-driven decision-making, working under guidance from senior engineers and architects. This position is part of the Global IT organization supporting SCIEX, Molecular Devices, and the Life Sciences Platform. This position reports to the Senior Manager - IT Applications and will be fully remote from India. In this role, you will have the opportunity to: - Develop and support data pipelines using Azure Data Factory and Microsoft Fabric. - Build and maintain database objects (tables, views, stored procedures) in Azure SQL Database, Microsoft Fabric, and Snowflake. - Monitor and troubleshoot production data pipelines and data warehouse processes. - Provide operational support for analytics and data warehouse requests from business users. - Maintain technical documentation and follow established development and version-control standards. Qualifications - 3+ years of experience developing or supporting data warehouse or analytics solutions. - Hands-on experience with ETL/ELT tools such as Azure Data Factory and/or Microsoft Fabric. - Experience working with cloud data platforms (e.g., Azure SQL Database, Snowflake). - Strong SQL development skills, including query development and basic performance tuning. - Experience supporting production data pipelines, including monitoring and resolving data issues. Requirements - Experience working with Oracle ERP EBS data models. - Experience collaborating with offshore or distributed development teams. - No travel required; occasional collaboration across time zones may be expected. Benefits - Join our winning team today. - Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. - We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

Role Description We are looking for an experienced Product Owner with strong expertise in Snowflake or Databricks to lead the delivery of an enterprise data lake initiative. This role requires a mix of product ownership, technical understanding, and data platform experience. The ideal candidate will work closely with engineering, architecture, and business teams to translate requirements into actionable deliverables and ensure successful rollout of a scalable data platform. - Lead the delivery of an enterprise data lake built on Snowflake or Databricks from initial setup to production deployment. - Translate business and data requirements into clear user stories, acceptance criteria, and sprint plans. - Drive the creation of data ingestion and integration pipelines from SaaS applications and other enterprise systems. - Manage the full development lifecycle, ensuring milestones and deliverables are completed on time. - Prioritize the product backlog based on business value, technical feasibility, and operational needs. - Build and maintain a detailed delivery roadmap, including MVP and phased releases. - Collaborate with cloud infrastructure and DevOps teams to ensure scalable, secure, and cost-effective environments. - Track and report key performance indicators such as pipeline success rates, data processing speed, and platform reliability. - Ensure smooth handover to analytics and data science teams with proper documentation and operational readiness. Qualifications - Proven experience as a Product Owner or Product Manager in data platforms, analytics, or cloud-based systems. - Strong understanding of Snowflake or Databricks including data modeling, pipelines, and cloud architecture. - Experience working with engineering, data, and DevOps teams in Agile environments. - Ability to translate complex business needs into technical execution plans. - Familiarity with data ingestion, ETL or ELT workflows, and API based integrations. - Strong communication skills and the ability to collaborate with cross-functional stakeholders. - Previous experience in HRMS or large-scale enterprise environments is an advantage.

Role Description Client is seeking a skilled AI/ML Data Engineer to support a large-scale finance optimization initiative focused on automation, data modernization, and AI enablement. This role will partner closely with finance and technology teams to design, build, and scale intelligent solutions that improve efficiency, accuracy, and insights across the organization. - Partner with finance stakeholders to analyze and optimize high-volume processes, including ~5,000 journal entries. - Design and implement AI-driven solutions, including LLM-powered agents, to automate complex data extraction and workflows. - Build, enhance, and maintain data models in Snowflake to support accurate and timely financial reporting. - Collaborate with cross-functional teams (software engineering, data engineering, and business teams) to deliver scalable solutions. - Leverage the Azure tech stack to design and deploy cloud-based data and AI solutions. - Ensure data quality, integrity, and usability across multiple business units and product lines. - Provide thought leadership on how AI can be effectively applied within finance operations. Qualifications - Strong experience in data engineering and/or software engineering with exposure to AI/ML. - Hands-on experience building or working with LLMs and AI agents. - Proficiency with Snowflake and modern data modeling practices. - Experience working within Azure cloud environments. - Ability to work cross-functionally and translate business needs into technical solutions. - Experience with data pipelines, transformation tools, and automation frameworks. Requirements - Background or experience working in finance or accounting environments. - Familiarity with financial systems, journal entries, or financial reporting processes. - Experience with or exposure to Alteryx or similar analytics tools. - Prior involvement in EPM system implementations or migrations.