As a Backend Developer, you will be responsible for developing and maintaining backend APIs and services using FastAPI and Flask-RESTX. You will design scalable, modular, and maintainable microservices-based solutions. Your role will involve working with PostgreSQL and MongoDB to create robust data models and efficient queries. Additionally, you will implement messaging and task workflows utilizing RabbitMQ and integrate secure authentication and authorization flows with Auth0. In this position, you will be required to monitor and debug production systems using Elasticsearch and APM tools. Writing clean, testable code and actively participating in design and code reviews will also be part of your responsibilities. Collaboration with cross-functional teams across engineering, DevOps, and product departments is crucial for the success of the projects. The ideal candidate must possess strong hands-on experience in Python backend development and practical knowledge of FastAPI, Flask, or Flask-RESTX. A solid understanding and real-world experience with microservices architecture are essential. Proficiency in either MongoDB or PostgreSQL, along with experience in RabbitMQ for async messaging and job queues, is required. Familiarity with API security and integration using Auth0 or similar services is also a must. Moreover, the candidate should have an understanding of observability practices utilizing Elasticsearch and APM tools. Strong debugging, performance tuning, and optimization skills are highly valued for this role. Experience with SQLAlchemy and Alembic for ORM and migrations, exposure to PostgREST or GraphQL APIs, and knowledge of containerized development with Docker are considered nice-to-have skills. Familiarity with CI/CD workflows, Git-based version control, and prior experience in event-driven, large-scale data processing systems would be advantageous.,
You will be joining a dynamic team dedicated to delivering custom and standard reports to clients using cutting-edge data visualization and reporting tools, primarily Power BI and SQL. As a talented and motivated Business Intelligence Analyst / Data Analyst, your key responsibilities will include designing efficient data models and relationships, collaborating with data engineering teams, optimizing DAX calculations and queries, resolving issues in data modeling and reporting, utilizing AI tools for productivity enhancement, automating reporting processes, and providing insights and recommendations based on data analysis to support business objectives. You should possess 4-8 years of business intelligence or data analytics experience with a must-have experience in Databricks. Additionally, you should have proven expertise in Power BI data modeling (Import, Direct Query, Composite models), strong skills in DAX, Power Query (M Language), and SQL, experience in big data reporting and handling large-scale datasets efficiently, ability to work independently with minimal supervision, strong problem-solving skills, experience with AI tools for efficiency improvement, knowledge of data warehousing concepts and ETL processes, and excellent communication and collaboration skills.,
As a Senior Data Analytics Manager at Skan, you will be responsible for transforming raw data into actionable intelligence that drives strategic decisions and enhances customer experiences. Your role will involve working at the intersection of cutting-edge analytics, business strategy, and customer success to convert complex datasets into descriptive and prescriptive insights that lead to measurable business outcomes. You will play a crucial role in designing and building advanced analytics frameworks, creating intuitive dashboards, and extracting critical insights that directly impact product evolution, customer success, and business growth. Your responsibilities at Skan will include: - Leading the analytics revolution by designing and implementing descriptive and prescriptive analytics - Architecting and delivering sophisticated customer-facing dashboards that highlight automation opportunities and performance metrics - Pioneering industry-specific analytics frameworks that demonstrate the transformative potential of AI in optimizing business processes - Conducting deep-dive analyses to uncover hidden patterns and trends, enhancing AI models and driving continuous product improvement - Enhancing data visualization to make complex insights immediately accessible and actionable - Partnering with customers to develop analytics solutions that deliver tangible ROI and align with strategic objectives - Collaborating across teams to influence Skan's AI platform roadmap based on real-world analysis and feedback - Championing data governance and establishing best practices for managing AI-generated insights - Driving innovation with data science teams to enhance machine learning models and develop advanced predictive and prescriptive analytics capabilities - Building and inspiring a high-performing analytics team that embodies ownership, intellectual curiosity, and AI-driven problem-solving Requirements: - 10+ years of hands-on leadership in business intelligence, advanced analytics, or data science - Expert-level proficiency in Databricks or Snowflake, Microsoft Power BI, and Tableau - Advanced SQL skills with substantial experience in modern data warehousing architectures - Strong Python capabilities for sophisticated data manipulation and transformation in AI/ML environments - Proven track record of creating intuitive, AI-enhanced dashboards that effectively communicate complex insights - Extensive experience in business process analysis and generating actionable intelligence for automation and optimization - Exceptional autonomy with the ability to drive projects independently while collaborating seamlessly across functions - Strategic analytical mindset focused on converting data into measurable business impact through descriptive and prescriptive approaches - Outstanding communication skills to translate complex AI-powered data narratives into compelling, strategic recommendations - Bonus experience in process mining, AI-driven analytics, value engineering, or automation intelligence If you are enthusiastic about shaping the future of AI-powered analytics, enjoy working hands-on with data, and seek to be part of a company that is redefining process intelligence through AI, this role at Skan is tailored for you.,
As a proactive and data-driven Sales Operations Manager at Skan, you will be instrumental in supporting the go-to-market teams throughout the revenue lifecycle. Your responsibilities will include critical tasks such as annual planning, pipeline performance analysis, lead allocation, CRM governance, sales program execution, and contracting process optimization. If you are passionate about delving into the sales tech stack and data, and are interested in contributing to the field of revenue operations, this role is well-suited for you. Your key responsibilities at Skan will include partnering with senior leadership from Sales, Marketing, Finance, and Revenue Operations to establish annual revenue targets by region, representative, and channel. You will assist in prioritizing markets and supporting Skan's go-to-market growth initiatives. Additionally, you will be responsible for designing and overseeing scalable workflows related to territory assignment, TAL-based lead allocation, representative specialization, and sales playbooks. Maintaining CRM hygiene, ensuring data quality, compliance with regulations like GDPR/CCPA, preventing duplicates, and ensuring email deliverability will also be part of your role. Collaborating with Sales and Marketing teams, you will design and refine lead-scoring and lifecycle models, monitor adherence to lead follow-up diligence, and address any identified bottlenecks in the pipeline efficiently. Leveraging AI workflows, you will streamline legal and contracting processes, such as contract review and redlining, in collaboration with the Sales team. To excel in this role at Skan, you should possess a minimum of 6 years of experience in Revenue Operations or Go-To-Market Strategy roles, preferably within the B2B SaaS industry. Strong familiarity with HubSpot CRM and a willingness to explore and implement tools that support revenue growth are essential. You should be open to understanding Skan's legal and contracting processes and demonstrate excellent analytical skills to translate data into actionable insights. Your ability to work effectively with cross-functional teams, including Sales, Marketing, Inside Sales, and Customer Success, and articulate complex concepts across various functions will be crucial. Experience in defining, overseeing, and optimizing sales territories and market segmentation, together with exceptional organizational skills, attention to detail, and proactive problem-solving abilities, are key attributes for success in this role. Your problem-solving skills, analytical mindset, and capability to execute plans and translate insights into actions will be valuable assets in driving Skan's revenue operations forward.,
As a skilled Data Engineer with 3 to 5 years of experience, you will be responsible for designing, building, and maintaining robust ETL/ELT pipelines using Databricks (PySpark/SQL). You will develop and optimize data workflows and pipelines on Delta Lake and Databricks Lakehouse architecture. Your role will involve integrating data from multiple sources to ensure data quality, reliability, and performance. Collaboration with data scientists, analysts, and business stakeholders will be essential to translate requirements into scalable data solutions. Monitoring and troubleshooting production data pipelines for performance and cost optimization will also be part of your responsibilities. Working with DevOps teams for CI/CD integration and automation of Databricks jobs and notebooks will be crucial, along with maintaining metadata, documentation, and versioning for data pipelines and assets. The ideal candidate for this position should possess 3 to 5 years of experience in data engineering or big data development. Strong hands-on experience with Databricks (Notebook, Jobs, Workflows) is required, along with proficiency in PySpark, Spark SQL, and Delta Lake. Experience with Azure or AWS, particularly Azure Data Lake, Blob Storage, Synapse, etc., is preferred. Strong SQL skills for data manipulation and analysis are necessary, as well as familiarity with Git, CI/CD pipelines, and job orchestration tools such as Airflow and Databricks Workflows. An understanding of data modeling, data warehousing, and data governance best practices is also expected.,