Job Summary We are seeking an experienced and highly skilled Senior Data Engineer to design, build, and maintain robust, scalable data infrastructure. You will play a key role in architecting data solutions, optimizing pipelines, ensuring data quality, and enabling data-driven decision-making across the organization. This role is ideal for someone who is passionate about data engineering, has strong problem-solving abilities, and can mentor junior team members while collaborating with cross-functional teams. Key Responsibilities Design and implement scalable and reliable data pipelines (batch and streaming) using technologies such as Spark, Kafka, and Airflow. Architect and maintain data warehouse/lakehouse solutions (e.g., Snowflake, BigQuery, Redshift, or Databricks). Build ETL/ELT workflows to ingest, transform, and validate data from various internal and external sources. Collaborate with data scientists, analysts, and software engineers to ensure data needs are met efficiently and securely. Optimize database performance and data workflows for reliability and low latency. Ensure data quality, governance, lineage, and security through best practices and tooling. Mentor junior engineers and contribute to engineering best practices, code reviews, and process improvements. Work with DevOps or Platform teams to automate deployment, monitoring, and alerting of data infrastructure. Maintain documentation of data architecture, systems, and processes. Required Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field. 7+ years of experience in Data Engineering or a related role. Strong proficiency in SQL and at least one programming language such as Python, Scala, or Java. Deep experience with data pipeline orchestration tools (e.g., Apache Airflow, Luigi, dbt). Hands-on experience with cloud platforms like AWS, GCP, or Azure, particularly with services like S3, Lambda, EMR, Glue, BigQuery, or Snowflake. Solid understanding of data modeling, data warehousing, and distributed computing systems (e.g., Hadoop, Spark). Experience with CI/CD practices and tools (e.g., GitHub Actions, Jenkins, Terraform). Strong understanding of data governance, including data privacy, compliance, and security best practices. Show more Show less

Job Overview As a Senior Cybersecurity Engineer, you will be responsible for designing, implementing, and maintaining robust security infrastructures to safeguard the organization's digital assets. You will lead initiatives to identify vulnerabilities, respond to incidents, and ensure compliance with industry standards and regulations. Key Responsibilities Security Architecture & Design: Develop and implement security solutions across IT and engineering environments, including firewalls, SIEM, IDS/IPS, and endpoint protection systems. Incident Response & Forensics: Lead investigations into security breaches, conduct root cause analysis, and develop mitigation strategies. Vulnerability Management: Perform regular vulnerability assessments, penetration testing, and manage patching processes to address potential threats. Security Monitoring: Oversee the deployment and tuning of security monitoring tools, ensuring effective detection and response capabilities. Policy Development: Create and maintain security policies, procedures, and documentation in alignment with industry standards like ISO 27001, NIST, and GDPR. Compliance & Audits: Ensure adherence to regulatory requirements and conduct internal audits to assess security posture. Team Leadership & Mentorship: Guide and mentor junior security engineers, fostering a culture of continuous improvement and learning. Stakeholder Collaboration: Work closely with IT, development, and operations teams to integrate security best practices into all aspects of the organization's infrastructure. Required Qualifications Education: Bachelor's degree in Computer Science, Information Technology, Cybersecurity, or a related field. Experience: Minimum of 7 years in cybersecurity roles, with a focus on engineering, architecture, and incident response. Technical Skills: Proficiency with security tools such as SIEM (e.g., Splunk, QRadar), firewalls, IDS/IPS, and endpoint protection systems. Strong understanding of network protocols, encryption methods, and secure application development principles. Hands-on experience with cloud security platforms (AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Scripting skills in languages like Python, PowerShell, or Bash for automation and tool integration. Certifications: Industry-recognized certifications such as CISSP, CISM, CEH, or GIAC are highly desirable. Preferred Qualifications Advanced Certifications: OSCP, GIAC Security Essentials (GSEC), Microsoft SC-200, or AZ-500. Specialized Knowledge: Experience with industrial control systems (ICS), OT security, and frameworks like IEC 62443. Analytical Tools: Familiarity with data analytics platforms like Tableau or Power BI for reporting and dashboard creation Show more Show less

Key Responsibilities Design, develop, and deploy machine learning models for prediction, recommendation, anomaly detection, NLP, or image processing tasks. Work with large, complex datasets to extract insights and build scalable solutions. Collaborate with data engineers to create efficient data pipelines and feature engineering workflows. Evaluate model performance using appropriate metrics and improve models through iterative testing and tuning. Communicate findings, insights, and model outputs clearly to non-technical stakeholders. Stay up to date with the latest machine learning research, frameworks, and technologies. Required Skills Strong programming skills in Python (Pandas, NumPy, Scikit-learn, etc.). Hands-on experience with ML/DL frameworks like TensorFlow, PyTorch, XGBoost, or LightGBM. Experience in building, deploying, and maintaining end-to-end ML models in production. Solid understanding of statistics, probability, and mathematical modeling. Proficiency with SQL and data manipulation in large-scale databases. Familiarity with version control (Git), CI/CD workflows, and model tracking tools (MLflow, DVC, etc.). Preferred Skills Experience with cloud platforms like AWS, GCP, or Azure (e.g., SageMaker, Vertex AI). Knowledge of MLOps practices and tools for scalable ML deployments. Exposure to real-time data processing or streaming (Kafka, Spark). Experience with NLP, Computer Vision, or Time Series Forecasting. Show more Show less

Key Responsibilities : Source and screen candidates through job portals, social media, referrals, and other hiring platforms. Conduct telephonic/virtual interviews to assess candidate suitability. Coordinate interviews between candidates and hiring managers. Follow up with candidates throughout the hiring process, including offer and onboarding stages. Maintain candidate databases and generate daily/weekly recruitment reports. Build and maintain a pipeline of qualified candidates for future hiring needs. Collaborate with department heads to understand hiring requirements and job specifications. Ensure all hiring processes comply with company policies and labor laws. Required Skills & Qualifications : Bachelor’s degree in Human Resources, Business Administration, or a related field. Excellent communication and interpersonal skills. Strong decision-making skills and attention to detail. Ability to work in a fast-paced environment with minimal supervision. Experience with ATS (Applicant Tracking Systems) and recruitment tools is a plus. Job Type: Full-time Pay: ₹12,000.00 - ₹20,000.00 per month Benefits: Provident Fund Schedule: Monday to Friday Night shift Supplemental Pay: Performance bonus Work Location: In person