Duties/Responsibilities: Weekly Enter time for all assigned accounts into VMS Software systems Weekly perform a reconciliation between Q4 and VMS Software for all accounts. Coordinate with account managers on workflow and issues that arise. Provide exceptional customer service to offices assigned to each account with clear concise correspondence of all adjustments and differences found. Required Skills/Abilities: Knowledge Prior VMS System a plus but not required. Skills Prior experience with excel. Excellent Customer Services skills required. Excellent organizational skills required. Abilities Ability to pick up new computer skills quickly, will be working with VMS systems with limited training. Ability to multi-task and adapt to changing priorities. Good attention to detail. Education and Experience: Some Accounting experience preferred. 1-2 years Customer Service Experience required. Problem resolution experience preferred Location – Vadodara, Gujarat Full Time (work from office- 5 days a week) Timings – 6.00pm to 3.00am IST – (8am to 5pm EST)
Key Responsibilities Design, deploy, and manage scalable, secure, and highly available cloud infrastructure on Azure. Collaborate with cross-functional teams to understand their technical needs and provide Azure-based solutions. Optimize cloud resources to ensure cost-efficiency and performance. Implement and manage Azure DevOps, including CI/CD pipelines. Monitor and maintain cloud systems to ensure optimal performance and security. Develop and maintain documentation for cloud solutions, configurations, and procedures. Troubleshoot and resolve issues related to cloud infrastructure. Stay updated with the latest Azure services, technologies, and best practices. Provide training and support to team members on Azure functionalities and best practices. Qualifications Bachelors degree in Computer Science, Information Technology, or a related field. Proven experience as a Cloud Engineer with a strong focus on Azure. In-depth knowledge of Azure services (e.g., Azure SQL, Azure Functions, Azure Kubernetes Service). Experience with cloud-based networking, security, and storage solutions. Hands-on experience with Azure DevOps, including pipeline creation and management. Proficiency in scripting languages such as PowerShell, Python, or Bash. Excellent problem-solving skills and the ability to work independently and in a team environment. Strong communication skills, both written and verbal. Azure certifications (e.g., Azure Administrator, Azure Solutions Architect) are highly desirable. Preferred Skills Experience with other cloud platforms (e.g., AWS, Google Cloud) is a plus. Knowledge of containerization and orchestration technologies (e.g., Docker, Kubernetes). Familiarity with Infrastructure as Code (IaC) tools like Terraform or ARM templates. Understanding of microservices architecture and serverless computing. Experience with monitoring and logging tools (e.g., Azure Monitor, Log Analytics).
Job Title: Senior Data Engineer Basic Function The Senior Data Engineer should be an expert familiar with all areas of data warehousing technical components (e.g., ETL, Reporting, Data Model), connected infrastructure, and their integrations. The ideal candidate will be responsible for developing the overall architecture and high-level design of the data schema environment. The candidate must have extensive experience with Star Schemas, Dimensional Models, and Data Marts. The individual is expected to build efficient, flexible, extensible, and scalable ETL design and mappings. Excellent written and verbal communication skills are required as the candidate will work very closely with diverse teams. A wide degree of creativity and latitude is expected. This position reports to the Manager of Data Services. Typical Requirements Requires strong technical and analytical skills, data management expertise, and business acumen to achieve results. The ideal candidate should be able to deep dive into data, perform advanced analysis, discover root causes, and design scalable long-term solutions using Databricks, Spark, and related technologies to address business questions. A strong understanding of business data needs and alignment with strategic goals will significantly enhance effectiveness. The role requires the ability to prepare high-level architectural frameworks for data services and present them to business leadership. Additionally, the candidate must work well in a collaborative environment while performing a variety of detailed tasks daily. Strong oral and written communication skills are essential, along with expertise in application design and a deep understanding of distributed computing, data lake architecture, and relational database concepts. This position requires the ability to leverage both business and technical capabilities regularly. Essential Functions Gather, structure, and process data from various sources (e.g., transactional systems, third-party applications, cloud-based financial systems, customer feedback, etc.) using Databricks and Apache Spark to enhance business insights. Develop and enforce standards, procedures, and quality control measures for data analytics in compliance with enterprise policies and best practices. Partner with business stakeholders to build scalable data models and infrastructure, leveraging Databricks' Delta Lake, MLflow, and Unity Catalog. Identify, analyze, and interpret complex data sets to develop insightful analytics and predictive models. Utilize Databricks to design and optimize data processing pipelines for large-scale data ingestion, transformation, and storage. Ensure data infrastructure completeness and compatibility to support system performance, availability, and reliability requirements. Architect and implement robust data pipelines using PySpark, SQL, and Databricks Workflows for automation. Provide input on technical challenges and recommend best practices for data engineering solutions within Databricks. Design and optimize data models for analytical and operational use cases. Develop and implement monitoring, alerting, and logging frameworks for data pipelines. Lead the architecture and implementation of next-generation cloud-based data solutions. Build scalable and reliable data integration pipelines using Databricks, SQL, Python, and Spark. Mentor and develop junior team members, fostering a data-driven culture within the organization. Develop high-quality, scalable data solutions to support business intelligence, analytics, and data science initiatives. Interface with technology teams to extract, transform, and load (ETL) data from diverse data sources into Databricks. Continuously improve data processes, automating and simplifying workflows for self-service analytics. Work with large, complex data sets to solve non-routine analysis problems, applying advanced machine learning and data processing techniques as needed. Prototype, iterate, and scale data analysis pipelines, advocating for improvements in Databricks data structures and governance. Collaborate cross-functionally to present findings effectively through data visualizations and executive-level presentations. Research and implement advanced analytics, forecasting, and optimization methods to drive business outcomes. Stay up to date with industry trends and emerging Databricks technologies to enhance data-driven capabilities. Specialized Skills or Technical Knowledge Bachelor's degree or higher in a quantitative/technical field (e.g., Computer Science, Statistics, Engineering). A Master's degree in Computer Science, Mathematics, Statistics, or Economics is preferred. 5+ years of experience in data engineering, business intelligence, or data analytics, with a focus on Databricks and Apache Spark. Extensive experience with SQL and Python for developing optimized queries and data transformations. Expertise in Databricks ecosystem, including Delta Lake, ML flow, and Databricks SQL. Experience in designing and implementing ETL/ELT pipelines on Databricks using Spark and cloud-based data platforms (Azure Data Lake, AWS S3, or Google Cloud Storage). Strong data modeling, data warehousing, and data governance knowledge. Experience in working with structured and unstructured data, including real-time and batch processing solutions. Familiarity with data visualization tools such as Power BI, Tableau, or Looker. Deep understanding of distributed computing, scalable data architecture, and cloud computing frameworks. Hands-on experience with CI/CD pipelines, Infrastructure as Code (IaC), and DevOps practices in data engineering. Proven track record of working with cross-functional teams, stakeholders, and senior management to deliver high-impact data solutions. Knowledge of machine learning and AI-driven analytics is a plus. Strong problem-solving skills and the ability to work independently and in a team-oriented environment. Excellent communication skills and ability to convey complex data concepts to non-technical stakeholders. Experience in a franchised organization is a plus.
RESPONSIBILITIES Process incoming payment files and provide notification to our franchisees of unapplied payments. Reconcile billing discrepancies and resolve customer inquiries related to invoices, payments, and account balances efficiently. Maintain detailed records of billing transactions, payments, and adjustments in the accounting system for audit readiness. EDUCATION & EXPERIENCE QUALIFICATIONS 1-2 years of experience in accounts receivable, billing, or data entry role, preferably in a high-volume transaction environment preferred. KNOWLEDGE, SKILLS, OR ABILITIES Apply analytical problem-solving skills to research payment exceptions, resolve discrepancies, and make informed decisions under unclear or changing conditions while maintaining data accuracy. Experience exhibiting strong customer service and communication skills to handle high-volume franchisee inquiries professionally, provide clear resolutions, and maintain positive relationships. Manage time and organize tasks effectively to prioritize daily activities, such as cash processing and customer support, and meet deadlines during high-pressure periods like month-end closings. Maintain confidentiality and exercise discretion with sensitive financial data, adhering to strict protocols and sharing information only with authorized personnel. Identify and correct errors using sound judgment to minimize impacts on reports or customer relationships, particularly in complex, non-standard situations. Role & responsibilities Preferred candidate profile