BENGALURU · FULLTIME
RA Analyst & Developer - Contractual

Titan Company
Bengaluru · onsite · Posted 13d ago
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Section · 01
About this role
As a Data Engineering Expert & Specialist at Titan Business, you will be responsible for designing and
implementing advanced Data Engineering techniques , designing Data Pipelines on vast datasets. Your primary
objective will be to extract meaningful insights, identify patterns, and deliver business rules, KPIs , Revenue
leakage from the transactions to drive informed business decisions and optimize operational efficiency.
Key Responsibilities:
- Design, develop, and maintain scalable data pipelines using PySpark, Python, SQL, Apache Spark, and cloud-based data
platforms to analyze 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.
•
External Interfaces Internal Interfaces
- Consulting Organisations
- Retail stores and our associate partners
- Working with our internal Finance team • Commercial teams in the divisions • Working with our Regional Commercial teams
Job Requirements
Education • BTech Graduate in Data Science & Machine Learning
Relevant Experience • 3 to 5 years
Behavioural Skills • Leadership abilities • Influencing skills • Self-starter • Inquisitiveness
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.
• Visualisation skills like Tableau / Power BI
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Section · 02
Skills
Section · Company
About Titan Company

Titan Company
Retail
9.0k+
employees
1984
42 years old
Bangalore, Karnataka
India
About
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Employee ratings
3,143 reviews
Culture
4.2
Career growth
3.4
Work-life
4.1
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