N Consulting Ltd

Role Description We are looking for a highly experienced Oracle Property Graph Database Specialist with 7–10+ years of experience in Oracle technologies and advanced data modeling. The ideal candidate will be responsible for designing and implementing graph-based data models aligned with complex network architectures. This role requires deep expertise in Oracle Database along with hands-on experience in graph technologies to enable relationship-driven analysis, network insights, and high-performance data processing. Key Responsibilities - Design and develop scalable graph data models (nodes, edges, properties) based on network architecture and system relationships - Implement and manage Oracle Property Graph solutions within the Oracle Database ecosystem - Convert relational and network data into graph structures for advanced analytics - Develop and optimize graph queries using PGQL (Property Graph Query Language) - Analyze and interpret network topology, connectivity, and dependencies using graph techniques - Collaborate with data architects, DBAs, and application teams to integrate graph solutions - Ensure performance tuning, scalability, and efficient data processing for large graph datasets - Support data migration, transformation, and validation processes - Provide technical guidance and best practices for graph-based implementations Qualifications - 7–10+ years of strong experience in Oracle Database development and administration - Hands-on experience with Oracle Property Graph and related tools (Graph Server, Graph Studio) - Strong expertise in SQL, PL/SQL, and Oracle data architecture - Proven experience in data modeling, including translating relational models into graph models - Experience working with network-based data structures (telecom, infrastructure, or similar domains) - Strong understanding of graph concepts such as traversal, pathfinding, and relationship analysis - Ability to design efficient and scalable graph schemas Salary Best market rate

Role Description We are seeking a talented individual to join our team in a data-driven capacity. The successful candidate will play a crucial role in interpreting data and delivering insights that drive business decisions. - Collect, clean, and analyse data from various sources. - Develop and maintain dashboards and reports to communicate findings. - Collaborate with cross-functional teams to understand data needs and provide analytical support. - Identify trends and patterns in complex datasets to inform strategic decisions. - Present findings to stakeholders in a clear and compelling manner. Qualifications - Proven experience in a data analysis role or similar. - Strong proficiency in statistical analysis tools and software (e.g., Excel, SQL, R, Python). - Excellent problem-solving skills and attention to detail. - Ability to communicate complex data insights to non-technical audiences. - A degree in a relevant field such as Mathematics, Statistics, or Data Science. Requirements - Experience with data visualisation tools (e.g., Tableau, Power BI). - Knowledge of machine learning techniques. - Familiarity with big data technologies (e.g., Hadoop, Spark).

Role Description Need experience in Implementation/Support Project with below Areas of MDG as MDG Technical Consultant: - Field Validations, Derivations in MDG MM/BP (Customer, Supplier) / FI - Dynamic and Normal Workflows in MDG BRF - Experience in BRFPlus workflows and Validations - Web Service Calls to Initiate the Change Request (SOAP) - Initiation of Customer/Material/Supplier CRs as Follow up CRs - Changes in UI (Field and Entity addition) with different Options, including Adaptation, feeder and Access Class - Experience in Data Replication (DRF) using IDOCs, SOAP - DQM Validations/Derivations in Mass Processing and Consolidation - Exposure/Experience in CDS Views and Fiori Apps - Knowledge in Odata Services - Experience in ABAP Coding Qualifications - Strong stakeholder communication, requirement elicitation, and workshop facilitation - Analytical problem-solving, structured documentation, and mentoring juniors - Ability to work in global delivery models and manage offshore/nearshore collaboration Requirements - MDG Consolidation & Mass Processing experience (match/merge, best record, Survivorship rules) - SAP MDG on BTP / cloud integration exposure

Role Description We are looking for an experienced Dynatrace Engineer for a 6-month contract opportunity in Basildon, UK. - Build and manage CI/CD pipelines - Support containerized deployments using Docker and Kubernetes - Work closely with development and operations teams - Monitor application and infrastructure performance using Dynatrace - Troubleshoot deployment and performance issues - Maintain Agile workflow tracking through Jira Qualifications - Excellent proficiency in CI/CD using Jenkins and GitLab - Strong experience with Jira and Git - Hands-on experience with Docker and Kubernetes - Good understanding of DevOps practices and deployment automation - Experience with monitoring, troubleshooting, and production support - Strong communication and collaboration skills Requirements - Experience with cloud platforms such as AWS, Azure, or GCP - Exposure to microservices architecture - Knowledge of automation and scripting

Role Description Guidewire Consultant - Maintenance, configuration, and support of Guidewire applications - Support of Incidents, Problems & Service Requests assigned to the Application Support Team - Client and Third-party communication on a day-to-day basis - Incident analysis and root cause finding for production incidents - Providing assistance and leadership to junior team members - On-call support, requiring availability beyond standard hours to promptly handle technical matters - Flexibility between tasks Qualifications - Excellent expertise in Property and Casualty Insurance - Excellent knowledge of Guidewire PolicyCenter & BillingCenter application OnPrem and Cloud versions - Provide technical expertise in Guidewire PolicyCenter, BillingCenter and GOSU language - Providing post-implementation support, enhancement and maintenance support and writing operational documentation - Providing domain and functional knowledge training to the team members - Strong learning and analytical skills - Strong coding experience in writing production data fixes and SQL knowledge - Good verbal and written communication skills - Guidewire certifications up to ACE/Profession in configuration / Integration Requirements - Contract/Perm - Remote work mode Benefits - Salary: 500 - 550 GBP Per day

Role Description We are seeking a Database Business Analyst to support the integration of database systems as part of the merger activity. The role will focus on: - Discovery and understanding current state database landscapes - Defining integration requirements - Identifying dependencies and risks - Partnering closely with stakeholders, project teams, and DBAs to enable a smooth and secure transition Qualifications - 6+ years of experience as a Business Analyst, with strong focus on database system integrations and mergers - Hands-on experience working with relational databases (Oracle, SQL Server, PostgreSQL, MySQL, etc.) - Strong understanding of data integration, data migration, and system dependencies - Experience supporting M&A, platform consolidation, or large-scale integration programs - Proficiency in requirements documentation (BRDs, FRDs, user stories, data dictionaries) - Strong analytical, communication, and stakeholder management skills - Detail-oriented with a strong focus on data accuracy and dependency mapping Requirements - Experience working with DBAs and data architects - Knowledge of data governance, security, and compliance considerations - Experience with Agile and/or Waterfall delivery models - Tools: Jira, Confluence, Visio/Lucidchart, SQL (read only/analysis) Benefits - Locations: Chennai, Pune, Hyderabad, Bangalore - Timings: 7.30 pm to 3.30 am - Remote - Salary: 1200000 - 1500000 INR Per annum

Role Description - Snowflake Developer with SSIS - Location: Poland (Remote) - Contract Role: 6-12 months contract Primary Skillset: - Data Modeling & ETL: - Design, develop, and optimize data models and ETL processes using Snowflake for efficient data storage and analytics. - Design and implement end-to-end ETL pipelines for loading data from various sources into Snowflake. - Utilize Snowflake’s built-in features such as tasks, streams, and Snowpipe to automate the ETL process for continuous and batch data loads. - Implement data transformation logic using SQL, Snowflake Stored Procedures (SQL and Python), and ETL tool to ensure the integrity, accuracy, and consistency of data. - Optimize data loads and transformations for scalability and performance using Snowflake’s micro-partitioning and clustering features. - Optimize and tune Snowflake queries, Data Storage, Warehouse for performance and efficiency. - Migration & Integration: - Experience with data migration, particularly from SQL Server to Snowflake, and integrating Snowflake with other data sources. - Collaborate with data architects and business stakeholders to understand data requirements. - Develop and maintain documentation for data processes and solutions. - Ensure data quality, governance, and security within the Snowflake environment. - Troubleshoot and resolve issues related to the Snowflake data warehouse. - Stay updated with the latest Snowflake features and best practices. - API Integrations: - Work on integrating Snowflake with external APIs for seamless data extraction and transfer. - Design, develop, and maintain SSIS ETL packages for complex data integration and transformation requirements. - Support existing SSIS packages during US off-hours. - Make updates to SSIS packages to add additional fields to be extracted. - DevOps Integration - Secondary: - Azure DevOps Experience: - Source control management. - Automating deployments. - Deploying Snowflake scripts across different environments. - Managing ETL pipeline deployments. - Proficiency in DevOps tools and best practices, with experience deploying Snowflake and ETL tool services. Qualifications - Proven experience as a Snowflake Developer with hands-on experience in Snowflake data warehousing solutions. - Strong understanding of Snowflake platform features, including micro-partitioning, file processing from AWS S3, and data quality practices. - Expertise in writing and optimizing SQL queries, including complex queries, CTEs, and stored procedures (using JavaScript within Snowflake). - Solid experience in working with Snowflake’s micro-partitioning, file processing from AWS S3, and optimizing data models. - Strong knowledge of Python for data engineering tasks and automation. - Background in data migration, specifically from SQL Server to Snowflake. - Familiarity with designing and managing data pipelines and ETL processes. - Excellent communication skills and the ability to collaborate effectively with cross-functional teams. Preferred Skills - Experience in using ETL tools like DBT/SnapLogic/Talend/Informatica/Fivetran for building ETL pipelines, testing, and deploying transformation models. - DBT/SnapLogic is preferred. - Strong knowledge of Snowpark for building scalable data pipelines and implementing advanced analytics workloads. - Hands-on experience with AWS services and DevOps tools (e.g., CloudFormation, Terraform) for deploying AWS resources such as Lambda, SQS, and SNS. - Familiarity with legacy Microsoft SQL platforms and integrating these with modern cloud-based data solutions. - Strong problem-solving skills and the ability to thrive in a collaborative and fast-paced environment. Salary - 1200 - 1300 PLN Per day

Role Description - Design, develop, and maintain automation workflows using Windmill and TypeScript - Build and integrate secure REST API integrations, including OAuth 2.0 flows - Implement robust error handling, exception management, retries, and logging mechanisms - Orchestrate complex, multi-step automation workflows across systems and services - Develop and optimize PostgreSQL queries for: - Automation execution logging - Operational reporting - Audit and tracking purposes - Own and support production automations end to end, including: - Monitoring and alerting - Incident troubleshooting and root cause analysis - Performance tuning and stability improvements - Lead and execute the migration of existing Ansible automations to the Windmill platform - Ensure automation reliability, scalability, and compliance with enterprise standards - Collaborate with stakeholders to understand automation requirements and deliver solutions aligned to business needs Qualifications - Strong experience in automation development on the Windmill platform - Proficiency in TypeScript for workflow and automation development - Hands-on experience with REST APIs and OAuth based authentication - Solid understanding of workflow orchestration, scheduling, and dependency management - Experience working with PostgreSQL, including query writing and reporting - Proven experience in production support, monitoring, and incident management - Experience migrating or modernizing automations (e.g., Ansible to Windmill) - Strong problem-solving and troubleshooting skills - Ability to work independently with full ownership of automation solutions Preferred Qualifications - Experience supporting large scale or enterprise automation programs - Familiarity with automation observability, logging frameworks, and alerting tools - Exposure to CI/CD pipelines and release management for automation workflows - Experience working in regulated or high availability environments

Role Description CTO Platforms are currently seeking an experienced professional to join our team in the role of SVS Tech Project Manager. The role will report to the appropriate SVS Change & Transformation Lead working closely with Lead Engineers in the SVS, other CTO Change & Transformation roles and wider teams/stakeholders to deliver common objectives. - Responsible for the delivery of specific SVS strategic portfolio initiative(s) outcomes supporting business vision and purpose through complex and global change portfolios. - Support of strategic planning cycles across SVS change portfolio to ensure financial investment decisions support CTO Platforms long term strategy, risk appetite and align to CTO strategy and future business/customer needs. - Support development of business cases and benefit validation to support transformation, strategic initiatives and to support fast-paced business responses to emerging threats and opportunities. - Develop and drive regular engagement with stakeholders to influence and deliver your SVS vision and strategy owning 2026 & 2027 Planning and the prioritisation of any unfunded change backlog and submissions within your SVS. - Support the management of RAID across CTO Platforms by ensuring your SVS portfolio risks, issues and dependencies are managed effectively, and senior stakeholders are informed/updated where appropriate. - Own and deliver your Initiative level reporting including preparing SVS Governance forum packs and tracking actions ensuring the completeness, accuracy and timeliness of Clarity data for your SVS executing within CTO Governance standards, directing assurance activities and escalating non-compliance issues. - The role includes leadership of other Transformation & Change owners in your SVS initiatives. - Supporting management of your SVS portfolio budgets to ensure it meets spend and benefit realisation commitments including budget forecast & actuals/variance management. - Ensuring that your SVS delivers its committed outcomes by working with engineering teams to align supply to meet forecasted demand pipelines i.e., Benefits and OKRs delivered. - Ensure your SVS initiative portfolio is interlocked appropriately with other portfolios within CTO Platforms and other Technology programs with dependencies well understood and managed. Qualifications - 5-10 years initiative & portfolio management or relevant experience, ideally within Financial Services technology functions, working primarily with Engineering capabilities and engaging with senior executives. - Strong emotional intelligence and leadership: Navigate organisational complexities, foster a positive work culture, and lead teams effectively. - Proven experience of large-scale transformation. - Knowledge of portfolio and project management principles and practices. - Knowledge of JIRA, Clarity and Microsoft 365 toolkit required. - Excellent communication/presentation skills required. - Proven ability to articulate complex issues concisely, suitable for all levels of CTO Platforms. - Pro-active problem-solving skills, able to work under pressure to challenging timescales and deliver at pace. - Strong stakeholder management capability and excellent communication at all levels of seniority. - Detailed understanding of financial & strategy planning. - Experience working with annual operations plans and multi-$m global programs and initiatives. - Excellent commercial awareness and proven ability to develop multi-year business cases worth $50-100m. - Knowledge and understanding of the AI technology landscape and interested in Engineering. - Experience of working in a diverse global team. - Flexible and adaptable to changing activities, schedules, workloads and priorities that are potentially highly restricted in nature, unpredictable, wide-ranging, complex and time-sensitive requires the simultaneous handling of a broad range of issues. - Proven leadership & strong teamwork skills, seeking to influence within and outside of the team and successfully encourage teams to work together. - Experience of continuous improvement. Company Description

Role Description This role is responsible for developing industrialized optimisation and machine learning models as part of a full-stack product squad that delivers operations decision-support software. As a key member of a product squad and reporting to the Lead Product Data Scientist, a Data Scientist will: - Develop data pipelines, machine learning models, and complex optimization models in the ODS software product suite. - Oversee modelling and robust implementation of features contributing to an operations decision-support product. - Ensure that features integrate seamlessly into the product’s technical stack (data ingestion, user interface, orchestration) as well as the business process and use case. Accountabilities - Understand a business problem and its component processes end to end, identifying opportunities to make decisions more optimally leveraging decision-support tooling. - Conduct analyses and visualizations to identify valuable opportunities for decision-support and determine trade-offs between different potential feature implementations. - Prototype advanced machine learning and optimization models to prove the value of a use case and approach (in Python). - Deliver features to industrialize machine learning and optimization models in Python using best-practice software principles. - Build automated, robust data cleaning pipelines that follow software best-practices (in Python). - Implement integrations between the core algorithm (machine-learning or optimization) and a workflow orchestration paradigm such as Dagster. - Implement software in a cloud-based deployment pipeline with Continuous Integration / Continuous Deployment (CI/CD) principles. - Build logging, error handling, and automated tests (e.g., unit tests, regression tests) to ensure the robustness of operationally critical decision-support products. - Deliver features to harden an algorithm against edge cases in the operation and in data. - Conduct analysis to quantify the adoption and value-capture from a decision-support product. - Engage with business stakeholders to collect requirements and get feedback. - Contribute to conversations on feature prioritisation and roadmap, understanding the trade-off between speed vs. long-term value. - Understand and integrate the product into existing business processes, contributing to the development and adoption of new business processes leveraging a decision-support product. - Communicate feature and modeling approach, trade-offs, and results with the internal team and business stakeholders. Skills/capabilities - Strong knowledge of machine learning and optimization techniques, including supervised (regression, tree methods, etc.), unsupervised (clustering) learning, and operations research (linear, mixed integer programming, heuristics). - Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobi, etc.) to solve real-life problems and visualize the outcomes (e.g., seaborn). - Proficient in working with cloud platforms (AWS preferred), code versioning (Git), and experiment tracking (e.g., MLflow). - Experience with cloud-based ML tools (e.g., SageMaker), data and model versioning (e.g., DVC), CI/CD (e.g., GitHub Actions), workflow orchestration (e.g., Airflow/Dagster), and containerized solutions (e.g., Docker, ECS) is nice to have. - Experience in code testing (unit, integration, end-to-end tests). - Strong data engineering skills in SQL and Python. - Proficient in the use of Microsoft Office, including advanced Excel and PowerPoint skills. - Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights. - Understanding of the trade-offs of different data science, machine learning, and optimization approaches, and ability to intelligently select the best candidates to solve a particular business problem. - Able to structure business and technical problems, identify trade-offs, and propose solutions. - Communication of advanced technical concepts to audiences with varying levels of technical skills. - Managing priorities and timelines to deliver features in a timely manner that meet business requirements. - Collaborative team-working, giving and receiving feedback, and always seeking to improve team processes. Qualifications - Master’s degree or greater in data science, ML, or operational research, or 2+ years of highly relevant industry experience (required). - 0-2 years working on production ML or optimization software products at scale (required). - Experience in developing industrialized software, especially data science or machine learning software products (preferred). - Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred). Key interfaces - Lead Product Data Scientist - Other Data Scientists - Business stakeholders and users - Software engineers (front-end, back-end, DevOps, data engineers) - Product & change managers - BA Digital teams (e.g., architects, application support managers) - External partners and third parties, as required - ODS Leadership (Head of Data & Analytics, Head of iOps & Optimisation, Director of ODS) Key performance indicators - Model accuracy, performance, and runtime (precision, recall, accuracy) - Time to develop and deploy features and models - Data ingestion & processing efficiency and robustness - Code quality and robustness (e.g., unit test coverage) - Collaboration and cross-functional teamwork Behaviours and attitude - I’m a role model for all BA brand behaviours and ways of working – I walk the talk. - I exude a can-do attitude (best of BA). - I’m flexible and agile, always ready to adapt when things don’t go to plan. - I’m an ambassador for BA and my team. - I role model our Leadership Behaviours. Core traits - Systems thinking - Detail oriented while understanding the big picture - Curious, self-motivated, proactive, and action-oriented - Creative and innovative - Resilient and flexible in light of changing priorities and approaches - Data-driven - Pragmatic - Collaborative - A true believer in the power of using data to drive better decision making - A technologist, interested in keeping up with the latest and greatest in software development, optimization, and machine learning - Commitment to delivering business value Interview Questions Ask the candidate the following questions and share the summary along with the candidate resume: - Tell me about an optimisation problem you have solved? - What was the business problem and the context of it? - Explain what the measure was? - What were the constraints? - Which algorithm did you use to solve this? - What was your end result?