Business Analyst

We're hiring a Data Analyst to turn raw data into clear, actionable insight. You'll partner with product, sales, marketing, and operations teams to answer their most important questions with data — building dashboards, running deep-dive analyses, and defining the metrics the business runs on. The ideal candidate is fluent in SQL, comfortable wrangling messy datasets, and just as strong at telling the story behind the numbers as they are at producing them. You'll own the accuracy and trustworthiness of the reporting stakeholders rely on to make decisions.

Key Responsibilities

• Design, build, and maintain dashboards and recurring reports across business functions
• Write and optimize SQL queries to extract, join, and transform data from multiple sources
• Run ad-hoc and deep-dive analyses to answer specific business questions
• Define, document, and standardize metrics and KPIs alongside stakeholders
• Investigate data-quality issues and ensure the numbers people see are accurate
• Translate analysis into clear recommendations and present them to non-technical audiences
• Support experimentation and A/B test analysis where relevant
• Automate repetitive reporting to free up time for higher-value analysis

Requirements

• 3+ years in a data analyst or business-intelligence role
• Strong SQL and hands-on experience with Power BI and/or Tableau
• Working knowledge of Python (pandas/numpy) for analysis
• Solid grounding in statistics and analytical methods
• Advanced Excel and strong data-visualization / storytelling skills
• Ability to work independently with stakeholders across functions

Nice to have

• Experience with cloud data warehouses (BigQuery, Snowflake, Redshift)
• Exposure to dbt or other ETL/transformation tooling

The Power BI Intern will assist the analytics team in using Microsoft Power BI to create interactive dashboards and reports. Working with actual datasets to assist well-informed business decision-making, this position provides practical exposure to data analysis, visualization, and business intelligence techniques.

Position title: Business Intelligence and Data Analyst

Summary -

• Operate and continuously improve the CARS/BI backend within the global Enterprise Data and Business Intelligence platform, ensuring system stability, continuous data loading, and Warehouse the timely delivery of business-critical reports.

• Own the underlying data foundation — SQL pipelines, relational data models, and data warehouse structures — that internal reporting teams and global Data Management initiatives depend on, and act as 1st and 2nd level support for internal customers such as SCM and Sales.

• The role is needed to secure daily BI availability in the Asian time zone, reduce the risk of late or incorrect reporting, and add dedicated database and ETL capacity to the global BI team, including support to the Data Centre team on infrastructure-related issues.

Responsibilities:

• Operate, monitor, and maintain the CARS/BI data integration and data processing workflows, ensuring continuous data loading and stable daily business operations.

• Provide 1st and 2nd level support for CARS/BI, including user support, incident handling, and root-cause analysis of data issues.

• Develop, maintain, and optimise SQL-based data pipelines and transformations within the Enterprise Data Warehouse.

• Design and maintain relational data models and data warehouse structures for CARS BI.

• Integrate data from ERP and other enterprise systems into the BI backend.

• Ensure data consistency, integrity, and performance at the database level, including query tuning and database efficiency improvements.

• Administer the BI technical environment and contribute to its continuous enhancement as part of a global team.

• Support reporting teams by providing structured, reliable datasets and safeguarding the timely delivery of business-critical reports.

• Contribute to global Data Management initiatives, with a focus on Master Data Management and the development of a Common Data Model within the Business Integration Platform.

• Collaborate with the Data Centre team to resolve infrastructure-related issues affecting BI availability.

Education and Experience:

Bachelor's degree in Engineering (BE/B.Tech) or equivalent in Computer Science, Information Technology, or a comparable technical field.

Minimum 3 years of relevant professional experience in Business Intelligence, data warehousing, or database development, including hands-on SQL and ETL work in an enterprise environment.

Experience supporting business users in a global or multi-time-zone IT organisation is an advantage.

Competencies:

• Knowledge about either BI platforms (e.g. IBM Cognos BI suite) or ETL tools (e.g. Informatica PowerCenter)

• Database, data modeling and SQL (preferred Oracle PLSQL)

• Good analytical and communication skills

• Teamplayer

• English

• Strong hands-on experience with SQL (advanced level)

• Solid understanding of relational databases and data warehouse concepts

• Experience with ETL tools and database technologies (e.g., Oracle, SQL Server, SAP BW,Informatica or similar)

• Performance tuning and query optimization skills

• Structured, detail-oriented, and quality-focused working style

• Good understanding of enterprise data flows (SAP/CARS is a plus)

Key Interfaces and Stakeholders:

Only internal customers with different topics: e.g. SCM, Sales etc.

Geography to cover and Travel requirements:

Asian Time Zone, Sometimes travel is required

Behavioral Characteristics

Reliability and accountability — the role safeguards daily reporting availability, so dependable ownership of monitoring and issue follow-up is expected. Structured, analytical problem solving with the patience for thorough root-cause analysis. Service orientation and clear communication towards internal customers such as SCM and Sales. Initiative taking and self-reliance, given largely independent work in the Asian time zone. Cooperation and team spirit within a globally distributed BI team across cultures and time zones. Flexibility and resilience under time pressure, including occasional off-hours support during critical data loads. Integrity and discretion when handling confidential business data. Quality focus and attention to detail, with a continuous improvement mindset.

Interview process

2 rounds - Virtual interview and 1 round Face to Face

Any other Criteria

• Notice Period: Below 60 or 90 Days . No Negotiation on Notice Period
• Gender: Female and Male; Female preferred
• Qualification:Bachelor's degree in Engineering (BE/B.Tech) or equivalent in Computer Science, Information Technology, 

This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.

Work Mode: WORK FROM OFFICE

Role Descriptions:

• Perform detailed data analysis and support business decision-making
• Gather and document business requirements and translate them into technical specifications
• Work closely with stakeholders to define data needs and reporting requirements
• Create user stories, functional specifications, and support UAT activities
• Ensure alignment between business objectives and data solutions

Required Skills:

• Strong expertise in SQL and data querying
• Proven experience in data analysis, requirement gathering, and stakeholder management
• Ability to translate business requirements into technical solutions and user stories
• Good understanding of data models, reporting, and analytics concepts

Skills: Business Analysis~ORACLE SQL

Locations: ~HYDERABAD~PUNE~

Desire candidate

• Candidate should have valid PF.

Key Responsibilities

• Collect, consolidate and manage data from various internal systems, SaaS platforms, CRM/ERP modules, logs, and databases.
• Generate daily, weekly, monthly, and ad-hoc MIS reports and dashboards for operations, sales, finance, customer-support or other relevant teams.
• Use advanced Excel to build, maintain, and manage complex spreadsheets — including pivot tables, VLOOKUP / HLOOKUP / INDEX-MATCH, SUMIF/COUNTIF, conditional formatting, charts/graphs, macros/VBA (if needed) to automate routine reporting tasks.
• Validate and clean data — ensure data integrity, consistency; identify and rectify discrepancies or anomalies.
• Collaborate with cross-functional teams (product, operations, support, finance, sales) to understand their data/reporting needs and deliver appropriate reports/insights.
• Provide ad-hoc data analysis or custom reporting as required by management or US stakeholders.
• Maintain documentation of reporting processes, data definitions/SOPs, report templates, and standard workflows.
• Ensure timely delivery of reports — especially considering night-shift schedule — so that US-based stakeholders receive data at start of their business day.
• Identify opportunities for process improvement and automation to make MIS reporting more efficient and reliable.

Required Skills & Qualifications

• Bachelor’s degree (in IT, Computer Science, Business, Statistics, or related field) or equivalent.
• Proven experience (1–3 years or as per company requirement) in MIS, data reporting/analysis, or similar role.
• Strong proficiency in Microsoft Excel — including advanced formulas/functions (VLOOKUP/HLOOKUP/INDEX-MATCH), pivot tables, charts/graphs, conditional formatting, data cleaning, data validation.
• Ability to build and maintain dashboards/reports; comfortable using Excel for recurring and ad-hoc reports.
• Strong analytical and problem-solving skills; ability to work with large datasets, identify trends, anomalies, and draw insights.
• Good communication skills — ability to coordinate with different teams/stakeholders, understand requirements, and present data/insights clearly.
• Readiness for night-shift work from office; ability to work independently, meet deadlines and manage time effectively.

Digital Mold Data Scientist and Manufacturing Analytics Specialist

Job Summary

COAST Systems is seeking a Data Scientist and Manufacturing Analytics Specialist in India to support a global client’s Digital Mold program.

This position will work with large and complex manufacturing, engineering, tooling, maintenance, and quality datasets. The successful candidate will transform fragmented operational data into reliable datasets, dashboards, actionable insights, and continuous-improvement opportunities.

This is a hands-on analytics role requiring close collaboration with engineering, manufacturing, operations, and business stakeholders. The position is particularly suited to someone who can understand a technical manufacturing problem, determine what the data is showing, and communicate practical recommendations that improve performance.

Key Responsibilities

• Collect, prepare, cleanse, normalize, and validate manufacturing and engineering data from multiple sources.
• Establish reliable and repeatable datasets for analytics, reporting, and decision-making.
• Analyze data to identify trends, risks, performance gaps, improvement opportunities, and potential cost savings.
• Develop and maintain dashboards, visualizations, KPI reporting, and business intelligence solutions.
• Analyze maintenance and operational performance using measures such as:
• Mean Time to Repair or MTTR
• Mean Time Between Failures or MTBF
• Overall Equipment Effectiveness or OEE
• Preventive and corrective maintenance performance
• Tool reliability, condition, quality, utilization, and lifecycle indicators
• Work closely with engineering and operations teams to convert technical and operational problems into data-driven solutions.
• Support continuous improvement, operational excellence, and process optimization initiatives.
• Align analyses and recommendations with client goals, priorities, and expected business outcomes.
• Identify relationships among tooling, maintenance, production, quality, sensor, and lifecycle data.
• Present findings clearly to technical and nontechnical stakeholders.
• Help establish consistent data definitions, analytical methods, and reporting standards.
• Support the development of predictive analytics, machine learning, and AI-enabled capabilities where appropriate.
• Learn the COAST software environment and relevant client or third-party systems.
• Help map and connect tool-specific data across systems so that information can be aligned and used consistently.

Required Qualifications

• Bachelor’s or master’s degree in data science, statistics, mathematics, computer science, engineering, operations research, or a related quantitative discipline.
• Strong data science and analytics experience involving large, complex, or multi-source datasets.
• Demonstrated experience with data preparation, cleansing, transformation, normalization, validation, and data-quality management.
• Strong statistical and analytical problem-solving skills.
• Proven experience developing dashboards, data visualizations, KPI reporting, and business intelligence solutions.
• Ability to analyze data and translate findings into clear, practical business or operational recommendations.
• Experience working with technical, engineering, operational, or business stakeholders.
• Strong continuous-improvement and process-optimization mindset.
• Ability to communicate clearly in English with global teams and client stakeholders.
• Ability to work independently, manage priorities, and investigate unclear or incomplete data.
• Strong attention to detail and commitment to data accuracy.

Preferred Qualifications

• Experience analyzing data in a manufacturing, engineering, maintenance, operations, or asset-management environment.
• Understanding of manufacturing equipment, tooling, maintenance, quality, and asset lifecycle concepts.
• Familiarity with MTTR, MTBF, OEE, preventive maintenance, reliability, and related manufacturing KPIs.
• Experience in plastics manufacturing or packaging, including any of the following:
• Injection molding
• Blow molding
• Extrusion blow molding
• Injection stretch blow molding
• Compression molding
• Other polymer-processing operations
• Experience working with cloud-based data platforms or data lake environments.
• Experience combining data from multiple software systems, databases, APIs, files, or vendor platforms.
• Experience with sensor, machine, equipment, IoT, or time-series data.
• Exposure to predictive analytics, machine learning, anomaly detection, forecasting, or AI applications.
• Experience developing analytics that lead to actionable workflows, reduced costs, improved reliability, or reduced manual effort.
• Experience supporting global organizations or working in a client-facing environment.

Technical Skills

Candidates should demonstrate proficiency in several of the following areas:

• SQL
• Python or R
• Statistical analysis
• Data preparation and transformation
• Data validation and data-quality analysis
• Dashboard and visualization development
• Power BI, Tableau, QuickSight, or a comparable BI platform
• Cloud data lakes or cloud analytics environments
• Relational and non-relational data sources
• Advanced Microsoft Excel
• Predictive modeling or machine learning
• API or multi-system data integration

Specific experience with every listed technology is not required. The candidate must, however, have strong foundational analytics skills and the ability to learn unfamiliar platforms and data environments.

Critical Competencies

• Analytical curiosity
• Structured problem-solving
• Systems thinking
• Data accuracy and attention to detail
• Continuous-improvement mindset
• Business and operational awareness
• Clear written and verbal communication
• Cross-functional collaboration
• Client responsiveness
• Adaptability and willingness to learn
• Ability to convert analysis into action

Experience

Approximately 4 to 8 years of relevant professional experience is preferred. Candidates with fewer years may be considered if they demonstrate strong hands-on analytics experience, manufacturing exposure, and the ability to work directly with engineering and operational stakeholders.

What Success Looks Like

The successful candidate will:

• Create trusted and repeatable manufacturing datasets.
• Deliver dashboards and reports that stakeholders actively use.
• Identify meaningful risks, trends, and improvement opportunities.
• Help engineering and operations teams make better decisions from their data.
• Improve the consistency of tool-specific information across systems.
• Progressively develop more advanced predictive and AI-enabled Digital Mold capabilities.
• Produce measurable improvements in reliability, operational performance, cost, and efficiency.

Suggested Key Skills

Data Science, Manufacturing Analytics, Data Analytics, Business Intelligence, Dashboard Development, Data Visualization, Power BI, Tableau, Amazon QuickSight, SQL, Python, R, Statistical Analysis, Data Cleansing, Data Normalization, Data Validation, Data Quality, Manufacturing KPI, OEE, MTTR, MTBF, Predictive Analytics, Machine Learning, Continuous Improvement, Process Optimization, Maintenance Analytics, Reliability Analytics, Cloud Data Lake, Sensor Data, IoT Analytics, Injection Molding, Plastics Manufacturing

About the Role

Work at the intersection of business and technology, supporting operations, data analysis, automation, and digital tools to improve efficiency and growth. 

 Responsibilities 

• Support business operations using tech tools (Excel, CRM, dashboards)  
• Analyze data and generate insights for decision-making  
• Assist in automation workflows and process improvements  
• Coordinate between tech and business teams  
• Help in implementing digital solutions and tools  

 Skills Required 

• Basic knowledge of Excel / Google Sheets  
• Good analytical and problem-solving skills  
• Understanding of business processes  
• Interest in technology and automation  

 Details 

• Duration: 3–6 months  
• Mode: Remote  
• Certificate + PPO based on performance