LogIQ Labs Pvt.Ltd.

1. Roadmap & Strategy (The "Why")

• Own the product roadmap for the Data Platform, prioritizing features like real-time ingestion, data quality frameworks, and self-service analytics.
• Translate high-level business questions (e.g., "We need to track customer churn in real-time") into technical requirements for ETL pipelines.
• Define Service Level Agreements (SLAs) for data freshness, availability, and quality.

2. Technical Execution (The "What")

• Write detailed Technical Product Requirements (PRDs) that specify source-to-target mappings, transformation logic, and API integration requirements.
• Collaborate with Data Engineers to decide on architecture trade-offs (e.g., Batch vs. Streaming, Build vs. Buy).
• Champion the adoption of Data Observability tools to detect pipeline failures before business users do.

3. Data Governance & Quality

• Define and enforce data modeling standards (Star Schema, Snowflake Schema).
• Ensure compliance with privacy regulations (GDPR/CCPA/DPDP) regarding how data is ingested, stored, and masked.
• Manage the "Data Dictionary" to ensure all stakeholders understand what specific metrics actually mean.

4. Stakeholder Management

• Act as the primary liaison between Data Producers (Software Engineers sending data) and Data Consumers (BI Analysts, Data Scientists).
• Manage dependencies: If the backend team changes a database column, ensure your ETL roadmap accounts for it.

🎓 What We Are Looking For

Technical "Must-Haves":

• SQL Mastery: You can write complex queries to explore data, validate transformations, and debug issues. You don't wait for an analyst to pull data for you.
• ETL Knowledge: Deep understanding of data integration concepts: Change Data Capture (CDC), Batching, Streaming, Upserts, and Idempotency.
• Data Modeling: You understand Dimensional Modeling, Data Lakes vs. Data Warehouses, and normalization/denormalization.
• API Fluency: You understand how to pull data from 3rd party REST/GraphQL APIs and handle rate limits/pagination.

Product Skills:

• Experience writing technical specs for backend/data teams.
• Ability to prioritize technical debt vs. new features.
• Strong communication skills to explain "Data Latency" to non-technical executives.

Preferred Tech Stack Exposure:

• Orchestration: Airflow, Dagster, or Prefect.
• Warehousing: Snowflake, BigQuery, or Redshift.
• Transformation: dbt (data build tool).
• Streaming: Kafka or Kinesis.

Role Summary

We are seeking a proactive and technically skilled Python Application Support Engineer to join our Technical Operations team. This role is crucial for ensuring the stability and reliability of our mission-critical, Python-based applications. You will be responsible for timely incident resolution, deep-dive troubleshooting, implementing permanent fixes, and driving operational efficiency through automation.

🔑 Key Responsibilities

Technical Troubleshooting & Incident Management

• Incident Resolution: Serve as the primary point of contact for complex Level 2 and Level 3 production incidents, diagnosing root causes and resolving issues across our Python application stack.
• Deep-Dive Analysis: Utilize log analysis tools (e.g., Splunk, ELK Stack) and monitoring platforms (e.g., Prometheus, Grafana) to quickly identify and address anomalies in application behavior.
• Code Debugging: Analyze, debug, and fix application issues directly within the Python codebase, including Flask/Django services, worker queues, and custom scripts.
• Database Health: Troubleshoot performance issues and conduct basic SQL/NoSQL query tuning and health checks (e.g., for PostgreSQL, MongoDB, or Redis).

Operational Excellence & Automation

• Monitoring & Alerting: Continuously refine and optimize application monitoring, alerting, and logging configurations to improve mean time to detect (MTTD) and mean time to resolve (MTTR).
• Python Automation: Develop, maintain, and enhance automated scripts (primarily in Python) to streamline routine operational tasks, reporting, health checks, and system recovery processes.
• Documentation: Create and maintain comprehensive documentation, runbooks, and knowledge base articles for application support procedures and recurring issues.

Collaboration & Prevention

• Cross-Functional Fixes: Collaborate closely with the Development and DevOps teams to provide clear technical feedback on recurring issues and implement permanent, scalable solutions.
• Proactive Maintenance: Identify potential system bottlenecks, performance degradation points, and areas prone to failure, recommending and implementing preventative measures.

⚙️ Required Qualifications

• Experience: 3 to 5 years of professional experience in Application Support, Production Support, Site Reliability Engineering (SRE), or a similar technical role.
• Python Expertise (Mandatory): Strong hands-on experience with Python scripting and programming, including the ability to read, debug, and modify application code.
• Operating Systems: Proficient working knowledge of Linux/Unix environments and shell scripting.
• Databases: Solid experience with relational (e.g., PostgreSQL, MySQL) and/or NoSQL (e.g., MongoDB, Redis) databases, focusing on query analysis and performance.
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Key Responsibilities

1. Team Leadership & Mentoring (30%)

• Mentorship: Lead, mentor, and coach a team of [X] Customer Success Associates. Conduct weekly 1:1s to review pipeline, blockers, and personal development.
• Escalation Management: Act as the primary point of escalation for critical client issues that your team cannot resolve independently.
• Performance Tracking: Monitor team KPIs (Time-to-Value, NPS, Response Time) and provide constructive feedback to ensure targets are met.

2. Strategic Reporting & Analytics (30%)

• Executive Reporting: Own the generation of weekly and monthly CS reports for the leadership team. This includes tracking Churn Rate, Net Revenue Retention (NRR), and Customer Health Scores.
• Forecasting: Analyze usage data to predict potential churn risks and identify upsell opportunities for the upcoming quarter.
• QBR Preparation: Standardize the template and data requirements for Quarterly Business Reviews (QBRs) across the team to ensure consistency.
• Data Integrity: Maintain hygiene in our CRM/CS Platform, ensuring all client interactions and health metrics are logged accurately.

3. Client Management (40%)

• Portfolio Management: Directly manage a portfolio of our High-Value/Enterprise clients, ensuring they achieve their desired business outcomes.
• Lifecycle Management: Oversee the end-to-end client journey for your accounts—from onboarding and training to renewal and expansion.
• Advocacy: Act as the Voice of the Customer (VoC) internally, collaborating with Product and Sales teams to prioritize features that reduce churn.

🎓 What We Are Looking For

• Experience: 5+ years in B2B SaaS Customer Success or Account Management, with at least 1 year of experience mentoring or leading a team.
• Data Proficiency: You love Excel/Google Sheets. You are comfortable using Pivot Tables and Lookups to crunch numbers and derive insights. (Experience with Tableau/PowerBI is a strong plus).
• Storytelling with Data: You don't just send a spreadsheet; you can look at the numbers and explain why a customer is at risk or where the expansion opportunity lies.
• Communication: Executive-level presence. You can command a room during a QBR and handle difficult conversations with unhappy clients.

We are looking for a versatile Project Business Analyst who can wear two hats. You will be the bridge between our business stakeholders and our technical teams. You won't just document requirements; you will own the delivery lifecycle.

In this role, you will translate business needs into technical specifications (BA) while simultaneously tracking timelines, managing scope, and ensuring the project stays on track (PM).

📋 Key Responsibilities

1. Business Analysis (The "What")

• Requirements Gathering: Conduct workshops and interviews with stakeholders to elicit, analyze, and document business requirements (BRD) and functional specifications (FRD).
• Process Mapping: Create detailed workflow diagrams, user journeys, and process maps using tools like Visio or Lucid chart to visualize current vs. future states.
• User Stories: Translate high-level business needs into actionable User Stories with clear Acceptance Criteria for the development team.
• UAT Coordination: Lead the User Acceptance Testing (UAT) phase, creating test plans and ensuring the final product meets business expectations.

2. Project Management (The "When" & "How")

• Sprint/Project Planning: Manage the project roadmap, facilitate sprint planning, daily stand-ups, and retrospectives (if Agile/Scrum).
• Timeline & Scope: Monitor project progress against deadlines, manage scope creep, and ensure deliverables are met on time and within budget.
• Risk Management: Proactively identify project risks or blockers and work with the technical team to resolve them before they impact the timeline.
• Stakeholder Communication: Act as the single point of contact for project status, providing regular updates (RAG status) to leadership and clients.

Market & Customer Intelligence

• Market Analysis: Conduct continuous research on the competitive landscape, market trends, and industry developments to identify opportunities and challenges.
• Customer Insights: Deeply understand target personas, their pain points, and how they use the product. Gather and synthesize qualitative and quantitative feedback from customers, sales, and support teams.
• Pricing Strategy: Collaborate with Product and Finance teams on pricing and packaging strategies based on market value and competitive analysis.

2. Positioning & Messaging

• Develop clear, differentiated, and compelling product positioning and messaging that resonates with target audiences and highlights unique value propositions.
• Create and maintain core messaging documentation (e.g., messaging matrices, key benefits, and use cases) for all product lines.

3. Product Launch & GTM Strategy

• Lead the planning and execution of comprehensive Go-to-Market strategies for new features and major product releases.
• Coordinate across departments (Sales, PR, Demand Generation) to ensure all teams are aligned on the launch plan, target audience, and messaging.
• Define the ideal customer journey and map marketing tactics to drive adoption and usage.

4. Sales Enablement & Content

• Create essential sales enablement tools and materials, including pitch decks, battle cards, competitive analysis guides, and demo scripts, to equip the Sales team for success.
• Develop customer-facing marketing content, such as website copy, landing pages, case studies, product videos, webinars, and technical blog posts, aligned with the messaging and SEO strategy.
• Train Sales, Support, and Marketing teams on new product features, value propositions, and successful objection handling.

5. Performance Monitoring

• Measure and analyze the effectiveness of marketing programs and product launches (e.g., adoption rates, conversion rates, and revenue impact).
• Use data to iterate on messaging, targeting, and GTM strategy for continuous improvement.

Required Qualifications

• Experience: 3-5 years of experience in Product Marketing, preferably for a SaaS, software, or technology company.
• GTM Expertise: Proven experience defining and executing successful Go-to-Market strategies and product launches.
• Content & Storytelling: Exceptional writing, communication, and presentation skills with a demonstrated ability to translate complex technical concepts into clear, engaging marketing stories.
• Technical Familiarity: Comfort with technology and the ability to work closely with Product Management and Engineering teams.
• Tools: Familiarity with CRM (e.g., Salesforce), Marketing Automation (e.g., HubSpot, Marketo), and Web Analytics tools (e.g., Google Analytics).
• Education: Bachelor’s degree in Marketing, Communications, Business, or a related field.

Key Responsibilities

• Prospecting: Identify and research potential clients (leads) using tools like LinkedIn Sales Navigator, Apollo, and ZoomInfo.
• Outreach: Execute high-volume outbound campaigns via cold calling, personalized emails, and social selling to connect with decision-makers.
• Qualification: Conduct initial discovery calls to understand customer pain points and determine if they are a good fit for our solution.
• Appointment Setting: Schedule product demos and meetings for senior Account Executives.
• Pipeline Management: diligently update and maintain lead activities in our CRM (e.g., HubSpot/Salesforce).
• Learning: Develop a deep understanding of our product, the market, and the competitive landscape.

🎓 What We Are Looking For

• Experience: 0–2 years of experience in Sales, Customer Support, or Business Development. (Freshers with excellent communication skills are welcome to apply).
• Communication: Exceptional verbal and written communication skills in English. You should be comfortable picking up the phone and talking to C-level executives.
• Grit & Resilience: Sales is about persistence. You should be able to handle rejection and stay motivated.
• Coachability: A hunger to learn and the ability to implement feedback quickly.
• Tech-Savviness: Comfortable working with software, CRMs, and productivity tools.

Development & Architecture

• Design, develop, and maintain robust, scalable applications using Java 8+ and the Spring ecosystem (Spring Boot, Spring Cloud).
• Implement and manage microservices architecture, ensuring services are secure, efficient, and adhere to best practices.
• Develop and integrate RESTful APIs to facilitate seamless communication between frontend systems, third-party services, and internal backend logic.
• Write comprehensive unit, integration, and end-to-end tests to ensure code quality and stability.
• Participate in code reviews, offering constructive feedback and ensuring adherence to development standards and architectural guidelines.

DevOps & Database

• Work with DevOps pipelines (CI/CD) to automate the building, testing, and deployment process.
• Manage relational and NoSQL databases, writing efficient SQL queries and optimizing data structures for performance.
• Troubleshoot and debug production issues quickly, identifying root causes and implementing hotfixes or permanent solutions.
• Utilize containerization technologies (Docker, Kubernetes) for development and deployment environments.

Collaboration & Documentation

• Collaborate effectively with Product Owners, Business Analysts, and QA engineers to translate requirements into technical designs.
• Maintain clear and concise technical documentation for new features, APIs, and deployment processes.
• Adhere to project timelines and milestones, providing accurate estimates for development tasks.

Required Technical Skills

• Core Java: 4+ years of hands-on professional experience with Java (preferably Java 11 or higher).
• Frameworks: Expert proficiency with Spring Boot for building production-ready microservices.
• APIs: Solid experience designing and consuming RESTful and/or SOAP APIs.
• Databases: Strong knowledge of SQL and experience with databases such as PostgreSQL, MySQL, or Oracle.
• Version Control: Expert use of Git in a team environment.
• Testing: Experience with testing frameworks like JUnit, Mockito, and integration testing tools.

The Python Support Engineer is responsible for providing Tier 2/Tier 3 technical support for our software applications and systems, focusing primarily on components built with Python. This role involves diagnosing and resolving complex production issues, performing Root Cause Analysis (RCA), developing temporary workarounds, and implementing permanent code fixes using Python.

🛠️ Key Responsibilities

1. Technical Support & Troubleshooting

• Diagnose and Resolve Issues: Act as the escalation point for complex technical issues related to Python applications, backend services (APIs), and data pipelines.
• Log and Data Analysis: Utilize advanced analytical skills and Python scripts (e.g., using Pandas or regular expressions) to parse system logs, database records, and monitoring data to pinpoint the root cause of failures.
• Debugging and Fixes: Read, understand, debug, and modify existing Python code to implement necessary bug fixes, patches, and minor enhancements.
• Database Interaction: Write and execute complex SQL queries to investigate data integrity issues and system performance problems across various relational (e.g., PostgreSQL, MySQL) and NoSQL databases.

2. Development and Automation

• Automation: Develop and maintain Python scripts and utility tools (e.g., using Bash/Shell scripting) to automate repetitive support tasks, streamline system health checks, and improve incident response efficiency.
• Monitoring and Alerting: Configure and fine-tune monitoring tools (e.g., Prometheus, Grafana, ELK stack) to proactively detect issues and ensure system reliability.
• Documentation: Create and maintain detailed technical documentation, including RCAs, knowledge base articles, runbooks, and troubleshooting guides for the support team.

Key Responsibilities

• Full Stack Development: Design, develop, test, and deploy robust, scalable applications using Java (Spring Boot) on the backend and Angular on the frontend.
• Backend & API: Build and maintain efficient, reusable, and reliable Java code. Design and implement RESTful APIs to support frontend applications and third-party integrations.
• Frontend Development: Develop modern, responsive, and intuitive user interfaces using Angular, TypeScript, HTML5, and CSS3.
• AWS Cloud Services: Leverage AWS services for application deployment, monitoring, and management. This includes working with services such as EC2, S3, RDS, Lambda, EKS/ECS, and CloudWatch.
• Database Management: Design and optimize database schemas (e.g., PostgreSQL, MySQL, or NoSQL) and write complex queries. Integrate with data persistence layers using JPA, Hibernate, or other ORMs.
• CI/CD & DevOps: Participate in and help improve our CI/CD pipelines for automated builds, testing, and deployments (e.g., using Jenkins, GitLab CI, or AWS CodePipeline).
• Code Quality: Write high-quality, clean, and maintainable code. Champion best practices in software development, including code reviews, unit testing, and integration testing.
• Mentorship: Provide technical guidance and mentorship to junior and mid-level developers.
• Collaboration: Work closely with product owners and stakeholders to understand requirements and translate them into technical specifications and solutions.

Required Skills and Qualifications

Experience:

• A total of 6-8 years of professional software development experience.
• At least 4-5 years of strong, hands-on experience with Java and the Spring ecosystem (Spring Boot, Spring MVC, Spring Data).

Technical Skills:

• Java/Backend:
• Proficient in Java 8 or higher.
• Deep understanding of Spring Boot, Spring Security, and REST API design.
• Experience with JPA/Hibernate and working with relational databases (e.g., PostgreSQL, MySQL).
• Strong knowledge of build tools like Maven or Gradle.
• Frontend:
• 2+ years of hands-on experience with modern Angular (Angular 8+).
• Proficiency in TypeScript, HTML5, CSS3, and SCSS/SASS.
• Experience consuming RESTful APIs from an Angular application.
• AWS:
• Demonstrable experience with core AWS services (S3, EC2, RDS).
• Hands-on experience deploying and managing applications on AWS.
• Familiarity with containerization (Docker, Kubernetes) and serverless (Lambda) is a significant plus.
• General:
• Strong understanding of software development life cycle (SDLC) and Agile methodologies.
• Proficient with Git and Git-based workflows.
• Excellent problem-solving, analytical, and communication skills.

We are seeking a curious and analytical AI/ML Data Analyst to join our growing team. This role is the perfect blend of deep data analysis, statistical modeling, and applied machine learning. With 3+ years of hands-on experience, you will be responsible for translating complex business questions into data-driven solutions.

You will work cross-functionally to mine massive datasets, perform exploratory data analysis, build predictive models, and generate actionable insights that drive product strategy, operational efficiency, and business growth. The ideal candidate has a strong statistical foundation and proven experience in applying ML models to real-world business problems.

<strong>Key Responsibilities</strong>

• Exploratory Data Analysis (EDA): Query, clean, and analyze large, complex datasets to identify trends, patterns, and anomalies.
• Predictive Modeling: Develop, train, and evaluate machine learning models (e.g., regression, classification, clustering, time-series forecasting) to solve business problems like customer churn prediction, fraud detection, or sales forecasting.
• Feature Engineering: Identify and create relevant features from raw data to improve model accuracy and performance.
• Data Manipulation: Write efficient and complex SQL queries for data extraction. Use Python (Pandas, NumPy) for advanced data manipulation, cleaning, and preparation.
• Insight Generation & Communication: Translate complex statistical and ML-driven findings into clear, concise, and actionable insights for non-technical stakeholders.
• Visualization: Create compelling dashboards and reports (using tools like Tableau, Power BI, or Python libraries) to communicate model results and analytical insights.
• Model Validation: Continuously monitor and validate model performance in production, suggesting improvements and retraining as needed.
• Collaboration: Partner with data engineers, product managers, and business stakeholders to define project requirements, gather data, and deploy solutions.