11+ Human Resource Management System (HRMS) Jobs in Mumbai | Human Resource Management System (HRMS) Job openings in Mumbai

HR Operations Executive

Location - Andheri, Mumbai

Work from office

10 am to 7 pm (Mon to Sat)

Please note only looking for an immediate joiner.

Requirements:

• Bachelor's degree in human resources.
• Minimum 3- 5 years of relevant experience in human resources.
• Additional training/certification in Payroll Management - may be advantageous.
• Full understanding of HR functions and best practices.
• Well-versed with HRMS
• Onboarding and Exit formalities
• Well-versed with the entire Payroll Cycle
• HR documentation
• Employee grievances
• Prepare and maintain employee master (MIS) (Good with excel)
• Good with drafting letters and policies

Job Description – ERP Coordinator (Independent Position)

Position: ERP Coordinator

Experience: 1+ Years

Location: Navi Mumbai

Industry Preference: ERP / Software / IT Services

Job Summary:

We are looking for an experienced and independent ERP Coordinator who can strictly monitor ticketing operations, coordinate between teams and clients, and ensure proper follow-up on every support and development query. The candidate should be confident, straightforward, result-oriented, and capable of handling responsibilities independently without continuous supervision.

Key Responsibilities:

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Monitor daily ERP support and development tickets.

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Ensure every client query is properly logged and ticket generated.

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Verify whether tickets are resolved within committed timelines.

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Follow up with support and development teams for pending issues.

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Track unresolved queries and escalate delays when required.

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Maintain proper coordination between client, support, and development teams.

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Ensure proper communication and status updates are shared with clients.

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Prepare daily/weekly pending ticket reports and management updates.

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Identify gaps in ticket handling and improve process discipline.

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Independently handle critical client coordination and issue management.

Required Skills:

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Strong experience in ERP coordination and ticket management.

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Good understanding of support flow, issue tracking, and escalation process.

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Strong communication and follow-up skills.

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Blunt, confident, and professional personality with strong ownership mindset.

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Ability to handle pressure and maintain strict process control.

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Experience with ticketing systems and ERP software preferred.

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Good reporting and documentation skills.

Candidate Profile:

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Independent decision-making capability.

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Strong work ethics and accountability.

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Ability to manage teams and push for timely closures.

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Professional attitude with excellent coordination skills.

Preferred:

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ERP implementation/support background.

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Experience working with multiple clients and internal technical teams.

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Ready to travel if required for business coordination.

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B.Com Graduate/ Any Gradute.

Must-Have Skills

• Minimum 3 years of experience in Data Engineering / Analytics Engineering / Fintech Data roles
• Must have worked on SMS Parsing, intelligent platform, converting RAW customer SMS data into structured actionable financial signals and enabling downstream usage of SMS derived variables
• Must have established a continuous learning cycle to expand parser coverage
• Experience in Lending / NBFC / Fintech domain
• Experience working with Bureau, SMS, Device, or Banking data
• Strong Python and SQL (production level)
• Experience handling unstructured data (SMS, logs, JSON, APIs)
• Experience building data pipelines, schedulers, and cron jobs
• Strong database design and data modelling skills
• Ability to work in a startup environment with high ownership
• Familiarity with modern platforms like AWS, Snowflake, Google BigQuery, Redshift

Good to Have

• Experience in STPL, especially less than 25K ticket size
• Experience with streaming (Kafka/Kinesis) and orchestration (Airflow or Step Functions)
• Experience with feature stores and risk analytics datasets
• Knowledge of regex, NLP basics for SMS parsing
• Experience supporting real-time decision engines/underwriting systems

Role Summary

This role will be responsible for owning the end-to-end data-structuring layer across the organisation. The individual will transform large volumes of raw, unstructured, and semi-structured data (such as SMS, device, bureau, and app data) into clean, standardised, and analysis-ready datasets. These structured datasets will directly power risk analytics, fraud detection, marketing insights, collections strategy, and policy decisioning.

Key Objective of the Role

Ensure all raw lending data (SMS, Bureau, Device, AA, App logs) is captured, parsed, structured, and stored in a clean analytics-ready format inside databases (PostgreSQL, DynamoDB, AWS stack) so that the Risk and Data Science team can directly use it for feature creation, policy building, and portfolio monitoring.

Core Responsibilities

1. End-to-End Data Ownership

• Design, build, and maintain end-to-end data pipelines (batch + streaming) using AWS native services (Glue, Lambda, Step Functions, Kinesis, S3, Athena, Redshift, EMR/Spark, etc.): ingestion

→ parsing → structuring → storage

• Work closely with Tech, Product, and Data Science to define what data should be captured
• Maintain data documentation, data dictionaries, and schema governance
• Ensure data quality, consistency, and version control

1. Unstructured Data Processing (Highest Priority)

• Parse raw SMS dumps and categorise into salary, EMI, loan apps, collections, credits, debits, OTP, etc.
• Process device fingerprint, behavioural logs, and vendor data (FinBox, AA, Bureau APIs)
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• Convert JSON, logs, and raw API responses into structured feature tables
• Build regex/keyword-based parsers for financial SMS classification

1. Feature Implementation (From Risk & Data Science Team)

• Implement feature creation logic provided by Risk/Data Science team
• Translate business and policy logic into SQL/Python pipelines
• Create reusable feature layers for underwriting, fraud, collections, and monitoring
• Maintain a feature store for consistent model and policy usage

1. Lending Data Understanding (Domain-Specific Requirement)

• Work with Bureau data
• Structure SMS-derived financial variables (income, stress, EMI signals)
• Work with Account Aggregator and bank transaction datasets
• Understand fintech alternate data used in underwriting and fraud detection

1. Data Pipelines & Automation

• Build and maintain ETL/ELT pipelines using Python & SQL
• Create cron jobs for automated data ingestion and feature refresh
• Automate vendor data pulls (Bureau, SMS SDK, AA, device data)
• Ensure low-latency pipelines for real-time underwriting use cases

1. Database Structuring & Storage Architecture

• Structure clean datasets in PostgreSQL (analytics layer)
• Manage raw data storage in DynamoDB / S3 data lake
• Design normalized and denormalised tables for risk analytics
• Optimise database performance for large-scale query workloads

1. Dashboards & Readable Data Layer

• Create analytics-ready datasets, implement & write Metabase queries and convert into dashboards (Metabase / Power BI)
• Enable self-serve data access for Risk, Business, and Founders
• Support ad-hoc analysis requirements from leadership

1. Cross-Functional Collaboration (Very Important)

• The role requires close collaboration with data science, tech, product, and business teams to ensure reliable data pipelines, well-defined schemas, API integrations, logging architecture and high data quality, enabling faster and more accurate decision-making across lending workflows.

Tech Stack (Current Environment)

• AWS Services
• PostgreSQL (Primary analytics DB)
• DynamoDB (Raw/NoSQL storage)
• Python (Pandas, NumPy, ETL frameworks)
• Advanced SQL
• APIs, JSON, and Log Data Handling

Role Overview

We are seeking an accomplished and dynamic Sales Manager based in Mumbai to lead TradeLab’s expansion across Western India. This is a high-impact, hunter-focused role tasked with building new client relationships with discount brokers, full-service brokers, banks, and fintech platforms. The role involves minimal account nurturing, with a primary focus on prospecting, pipeline development, and closing high-value deals. The ideal candidate will bring deep industry expertise, an established network in the capital markets, broking, and fintech sectors, and a proven ability to navigate complex sales cycles with senior stakeholders.

Key Responsibilities

• New Business Development: Drive aggressive acquisition of new clients across Western India by targeting entities aligned with TradeLab’s Ideal Customer Profile (ICP), including discount brokers, full-service brokers, banks, and fintech platforms.
• Pipeline Management: Build, manage, and maintain a robust sales pipeline by prospecting, qualifying leads, and advancing opportunities through discovery, demonstrations, proposal creation, negotiation, and deal closure.
• End-to-End Sales Ownership: Lead complex, enterprise-grade sales cycles from initial outreach to contract signing, engaging senior stakeholders such as CEOs, CTOs, CIOs, and Heads of Broking.
• Solution Positioning: Collaborate closely with solutions architects and product teams to tailor and position TradeLab’s modular offerings (ORMS, MetaTrader integrations, PULSE AI, CRM/LPA solutions) to address specific client pain points and objectives.
• Regulatory Expertise: Demonstrate a deep understanding of regulatory frameworks (e.g., SEBI guidelines, algo trading controls, T+0 settlement workflows) and articulate their business value to position TradeLab’s solutions as compliance-driven and operationally efficient.
• Brand Representation: Act as TradeLab’s ambassador at industry events, trade shows, webinars, and client meetings to enhance brand visibility and establish thought leadership in the capital markets ecosystem.
• Market Feedback: Provide actionable, structured insights from client interactions to influence product roadmaps, go-to-market strategies, and solution enhancements.
• CRM Management: Actively maintain and update customer relationship management (CRM) systems to ensure accurate tracking of leads, opportunities, and client interactions, enabling data-driven decision-making and forecasting.

Key Responsibilities

• Develop and implement a comprehensive L&D strategy aligned with business priorities and growth targets.
•  Act as a strategic advisor to senior leadership on talent development, succession planning, and sales readiness.       
• Promote a culture of continuous learning, high performance, and sales excellence.
• Build and maintain leadership pipelines, addressing critical skill gaps across the organization.
• Integrate market insights, product knowledge, customer-centric strategies, and competitive intelligence into learning journeys.
• Team Development: Build, mentor, and empower high-performing teams that are mission-aligned and impact-driven.

Key Competencies Required:

• Deep expertise in L&D strategy, payroll management, and talent acquisition.
• Ability to structure, monitor, and optimize team performance.
• Strong strategic thinking and ability to align HR initiatives with business objectives.
• Experienced in managing and developing large sales teams, driving capability and performance.

What you need to have: