Responsibilities: Assembling large, complex sets of data that meet non-functional and functional business requirements Design, develop, monitor and maintain scalable data pipelines and ETL processes Build required infrastructure for optimal extraction, transformation and loading of data from various data sources using Integration and SQL technologies, often these are Cloud based Identifying, designing and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes Building analytical tools to utilise the data pipeline, providing actionable insight into key business performance metrics Ensure data quality, consistency, integrity, and security across all systems Drive continuous improvement of data engineering best practices and tooling Required Skills and Experience: Bachelors Degree in Computer Science, Engineering, Mathematics, or related field 5-7 years of experience in a database management, data engineering or similar role Proficiency in programming languages such as Python or Scala Strong proficiency in SQL and experience with relational databases (e.g. MSSQL, PostgreSQL, MySQL) Hands-on experience with No-SQL database technologies Experience in database optimization and performance tuning required Good understanding of Data Integration patterns Exposure to BI tooling such as Power BI or Yellowfin is advantageous Experience setting up MS SQL Replication and Data Archiving strategies will be beneficial Experience with cloud platforms (e.g., AWS, GCP, Azure) and services like S3, Lambda, Redshift, BigQuery, or Snowflake Familiarity with big data technologies like Apache Spark, Data Bricks, and Hive Familiarity with data modelling, warehousing concepts, and data governance practices Exposure to Data cleansing and de-duplication techniques will be beneficial Advantageous: Experience with stream processing tools (e.g., Kafka, Spark Streaming, Flink) Knowledge of containerization (Docker) and orchestration tools (Kubernetes) Understanding of CI/CD principles and infrastructure-as-code Exposure to machine learning workflows and MLOps

Job Description Co-ordinating with site teams and management to ensure optimal service delivery and client satisfaction. Tracking and verifying that all cleaning and security tasks are completed according to the daily schedule. Monitoring live escalation triggers and addressing non-compliance with on-site teams. Monitoring Attendance in real-time by tracking and comparing actual hours worked against planned hours Ensuring all aspects of the cleaning and security services are tracked and delivered according to client requirements. Ensuring all planned maintenance tasks are entered into the system with appropriate alerts set. Analyzing variances and understanding reasons behind these variances such as overtime, absenteeism, understaffing and rostering inefficiencies as well as looking for trends for the above. Monitoring the completion of tasks logged in the system, ensuring timely execution. Ensuring that all contractual obligations to the client are met in accordance with SLA requirements. Regularly reviewing dashboards to monitor overall SLA and operational compliance. Qualifications & Skills Certification in Data Science, Computer Science, or a related field is required 2-3 years working experience in Data analysis, reporting, and data-driven decision making Experience in conducting trend analysis and statistical analysis to identify patterns and insights. Minimum of 2-3 years working experience with data visualization and dashboard tools (Power BI, ZOHO) Strong knowledge of Excel (advanced functions, pivot tables) Familiarity with business intelligence (BI) platforms Familiarity with Profit, Velocity, SAP, or similar operational systems (advantageous) Suitable candidates will be contacted. If you do not get a response within 14 days, please consider your application unsuccessful.