Primary Skills: Machine Learning, Optimization, Cloud Services (Azure/Oracle), MLOps. Secondary Skills: End-to-end data science projects, databases and pipelines, manufacturing domain Soft skills: Stakeholder management, leadership, proactive Note: Preference will be given to those with manufacturing domain experienced.
Key Skills & Competencies: Business & Analytical Skills Strong understanding of business processes across domains (finance, operations, sales, etc.) Experience with data governance, master data, and data quality frameworks. Ability to perform root cause analysis, gap assessments, and impact analysis. Technical/Functional Skills Working knowledge of SQL, Excel, and BI/reporting tools (Power BI, Tableau, Qlik, etc.) Understanding of data warehousing concepts, ETL processes, and cloud platforms (Azure, AWS, GCP). Familiarity with wireframing tools (Balsamiq, Figma, Lucidchart, PowerPoint, etc.) Exposure to Agile/Scrum delivery frameworks; writing user stories, epics, and acceptance criteria. Soft Skills Strong communication and presentation skills (verbal and written). Ability to manage multiple stakeholders and prioritize conflicting demands. Structured thinking, attention to detail, and a problem-solving mindset. Key Responsibilities: 1. Data Maturity & Strategy Lead or assist in conducting data maturity assessments across business units. Map the current state of data capabilities (people, processes, and technology) to target maturity levels. Identify data-related gaps, risks, and opportunities and suggest prioritized improvement areas. 2. Requirements Gathering & Analysis Conduct stakeholder interviews and workshops to understand analytics and reporting needs. Translate business requirements into functional and non-functional specifications. Define KPIs, metrics, and business rules in alignment with strategic goals. 3. Wireframing & Prototyping Create mockups, wireframes, or storyboard visuals for dashboards and reports. Collaborate with data visualization experts or BI developers to validate design feasibility. 4. Stakeholder & Communication Bridge Act as a bridge between business stakeholders and technical/data engineering teams. Facilitate clear documentation, user stories, and workflows to ensure alignment. Assist in user acceptance testing (UAT) and ensure solutions meet business needs. 5. Project Support Delivery Support project managers in tracking delivery timelines and scope. Ensure solutions are aligned to enterprise data strategy and governance standards. Participate in change management, training, and post-implementation support. 6. Analytics Technology Enablement Understand and document data lineage, source systems, and ependencies across the analytics tech stack. Assist in developing queries, DAX measures, or model definitions to support visualization and reporting needs. Collaborate with data engineers to define and test data pipelines, perform ad-hoc SQL queries, and troubleshoot data issues. Contribute to the evaluation and adoption of analytics platforms and tools (e.g., Power BI, Tableau, Snowflake, Azure, SQL).
Summary: We are seeking an experienced Power BI & Power Platform Analyst with 3+ years of expertise in designing, developing, and maintaining interactive dashboards, reports, and applications. The ideal candidate will have strong skills in Power BI, Power Apps, and other Power Platform components to deliver business insights and automation solutions that support organizational decision-making and process improvement. Key Responsibilities: Design, develop, and maintain Power BI dashboards, reports, and visualizations based on business requirements. Build efficient data models and DAX calculations within Power BI. Connect to various data sources (Excel, SQL, SharePoint, etc.) and transform data using Power Query. Ensure data accuracy, performance optimization, and visual consistency across reports. Collaborate with stakeholders to gather and refine reporting and automation requirements. Develop and support Power Apps for business process automation and workflow improvements. Integrate Power BI with Power Automate and other Power Platform tools to enhance business solutions. Implement role-level security, slicers, filters, and navigation for user-friendly reports. Maintain and update existing Power BI and Power Platform solutions as business needs evolve. Required Qualifications: 3+ years of hands-on experience with Microsoft Power BI and Power Platform. Strong expertise in creating complex Power BI reports, dashboards, and data models. Proficiency in DAX (Data Analysis Expressions) and Power Query (M language). New Position Requirement Experience in developing Power Apps (Canvas & Model-driven) and integrating them with other systems. Knowledge of Power Automate for workflows and process automation. Familiarity with Power BI Service: publishing, sharing, and scheduling reports. Solid understanding of database concepts and relationships. Strong problem-solving, communication, and stakeholder management skills.
,. Job Description: We are looking for an experienced Data Engineer with strong expertise in data pipeline development, cloud-based data processing, and analytics solutions. The ideal candidate should have hands-on experience working with AWS data services and be proficient in programming and data integration tools. Key Responsibilities: Design, develop, and maintain robust, scalable, and efficient data pipelines and ETL workflows. Work with large and complex datasets using Python and SQL for data transformation and analysis. Develop distributed data processing solutions using Spark (Scala or PySpark) Spark Scala preferred . Implement and manage AWS data services including S3, Lambda, Glue Crawlers, Athena, and EMR . Create and maintain data visualization and reporting solutions using Amazon Quicksight or similar BI tools. Ensure data quality, performance, and reliability across the data ecosystem. Monitor, optimize, and troubleshoot data workflows using CloudWatch and set up notifications with SNS . Collaborate with analytics, data science, and product teams to deliver high-quality data solutions. Required Skills: Must Have: Python, SQL, S3, Lambda, Glue Crawlers, Athena One of: Spark Scala / PySpark ( Scala preferred ) Highly Desirable: EMR, Quicksight Good to Have: SNS, CloudWatch