Data Engineer - Contract 7 month/ Immediate joiner

Key Responsibilities:
· Key Responsibilities
· Design, develop, and maintain scalable data pipelines using PySpark, Python, SQL, Apache Spark, and cloud-based data platforms to analyse large-scale datasets across the business value chain.
· Identify, quantify, and remediate revenue leakages, process inefficiencies, control gaps, and systemic issues impacting business performance, profitability, and customer experience.
· Perform end-to-end data analysis across commercial, operational, billing, finance, supply chain, and customer processes to uncover hidden revenue opportunities and operational risks.
· Build data-driven frameworks and controls to proactively detect anomalies, reconciliation breaks, process exceptions, and revenue assurance risks.
· Collaborate with business, operations, finance, technology, product, and compliance teams to understand business processes, map value streams, and identify opportunities for process optimization and control enhancement.
· Develop automated monitoring and reconciliation solutions using Python, SQL, PySpark, Airflow, and data quality frameworks to strengthen process governance and reduce revenue leakage.
· Design and implement robust ETL/ELT pipelines leveraging technologies such as:
· Utilize statistical analysis, data mining, anomaly detection, and AI/ML techniques to identify patterns, trends, fraud indicators, control weaknesses, and revenue-impacting exceptions.
· Schedule, orchestrate, and monitor batch and near real-time workflows using Apache Airflow, ensuring reliability, scalability, and operational excellence of critical business processes.
· Implement data quality, lineage, reconciliation, and observability frameworks to ensure accuracy, completeness, and consistency of enterprise-wide data assets.
· Partner with Data Engineering, Enterprise Architecture, and IT teams to integrate analytics and revenue assurance controls seamlessly into existing business and technology ecosystems.
· Create executive dashboards, KPI frameworks, and actionable insights using visualization tools such as Power BI, Tableau.
Knowledge :
· Analytical capability in bringing insights from data.
· Business acumen and strategic capability
· SQL & Complex SQL, Microsoft applications
· Proficiency in programming languages such as Python, or Java, and familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn). PySpark.
· Strong understanding of machine learning algorithms (e.g., regression, classification, clustering, deep learning) and their practical applications.
· Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms (e.g., AWS, Azure, Google Cloud Platform) capabilities of integrating AI Model over cloud.
· Excellent problem-solving skills and the ability to translate business requirements into technical solutions.

Work arrangement
No