Purpose of the role: To provide comprehensive and strategic legal support by leading the review, drafting, and management of agreements and legal documents across multiple business verticals within The Group. The Senior Manager will oversee corporate contracts drafting, coordination, negotiations and execution to safeguard and advance the company's legal interests. This role requires significant interaction with senior stakeholders and external partners, emphasising driving legal strategies aligned with business goals. Key Responsibilities: 1. Contract Management and Execution: Lead and manage the end-to-end process of reviewing, vetting, drafting, and negotiating contracts across various business divisions. Analyzing and reviewing existing and fresh contracts to ensure they comply with legal requirements and protect the company's interests. Negotiating contract terms with third parties to achieve mutually beneficial agreements. Provide strategic legal advice on complex agreements such as service agreements, technology agreements, privacy policies, lease deeds, and employment agreements. Collaborate with senior leadership to align contractual documents with business objectives and risk management strategies. Establish and maintain a robust contracts database and document management system. Ensure timely execution of agreements and maintain an audit-ready record of all legal documents. 2. Corporate Compliance and Governance 3. Litigation and Arbitration 4. Conduct regular legal risk assessments and recommend strategies to mitigate risks. 5. Provide leadership and guidance to contracts team members
THIS IS A FULLY REMOTE JOB WITH 5 DAYS WORK WEEK. THIS IS A ONE YEAR CONTRACT JOB, LIKELY TO BE CONTINUED AFTER ONE YEAR. Required Qualifications 8+ years of full-stack engineering experience, preferably with B2B or industrial applications Strong in Python + React + SQL stack Key Responsibilities Full-cycle application development : Own architecture, design, and deployment of industrial applications from UI to backend to database. Translate industrial use-cases into software : Partner with DS and DE teams to turn optimization models, GenAI prototypes, or ML algorithms into robust, user-facing applications. Industrial-grade integration : Connect with OT systems (e.g., DCS, PLC, SCADA), SAP, and plant historian data to enable real-time insights. Tech Stack Frontend React.js, TypeScript, Tailwind CSS Streamlit (for internal tools) Plotly / Recharts / D3 for visualizations Backend Python (FastAPI, Flask), Node.js Pyomo/OR-Tools (optimization) integration Real-time streaming via WebSockets or MQTT Databricks Databases PostgreSQL, SQLite, Supabase Time-series: InfluxDB, OSI PI, or Azure Data Explorer Blob/file: Azure Data Lake or S3
THIS IS A FULLY REMOTE JOB WITH 5 DAYS WORK WEEK. THIS IS A ONE YEAR CONTRACT JOB, LIKELY TO BE CONTINUED AFTER ONE YEAR. Required Qualifications Education: B.Tech /M.Tech in Computer Science, Data Engineering, or equivalent field. Experience: 7-10 years in data engineering, with 2+ years in an industrial/operations-heavy environment (manufacturing, energy, supply chain, etc.) Job Role Senior Data Engineer will be responsible for independently designing, developing, and deploying scalable data infrastructure to support analytics, optimization, and AI-driven use cases in a low-tech maturity environment . You will own the data architecture end-to-end , work closely with data scientists , full stack engineers , and operations teams , and be a driving force in creating a robust Industry 4.0-ready data backbone. Key Responsibilities 1. Data Architecture & Infrastructure Design and implement a scalable, secure, and future-ready data architecture from scratch. Lead the selection, configuration, and deployment of data lakes, warehouses (e.g., AWS Redshift, Azure Synapse), and ETL/ELT pipelines. Establish robust data ingestion pipelines from PLCs, DCS systems, SAP, Excel files, and third-party APIs. Ensure data quality, governance, lineage, and metadata management. 2. Data Engineering & Tooling Build and maintain modular, reusable ETL/ELT pipelines using Python, SQL, Apache Airflow, or equivalent. Set up real-time and batch processing capabilities using tools such as Kafka, Spark, or Azure Data Factory. Deploy and maintain scalable data storage solutions and optimize query performance. Tech Stack Strong hands-on expertise in: Python, SQL, Spark, Pandas ETL tools: Airflow, Azure Data Factory, or equivalent Cloud platforms: Azure (preferred), AWS or GCP Databases: PostgreSQL, MS SQL Server, NoSQL (MongoDB, etc.) Data lakes/warehouses: S3, Delta Lake, Snowflake, Redshift, BigQuery Monitoring and Logging: Prometheus, Grafana, ELK, etc.