:

1. Technical / Individual Contributor Responsibilities (80%)

Data Engineering & Integration

- Lead the hands-on development and delivery of end-to-end data engineering solutions, including requirements analysis, technical design, development, testing, deployment, and production support.
- Design, develop, optimize, and maintain ETL/ELT pipelines, data integration workflows, and enterprise data warehouse solutions using Databricks, PySpark, Azure Data Factory (ADF), SSIS, Informatica, SQL, and Python.
- Build scalable and reliable data processing solutions across cloud platforms and enterprise data environments.
- Develop and optimize complex SQL queries, stored procedures, Python scripts, and data transformation logic.
- Implement reusable frameworks, workflow automation, error handling, logging, monitoring, and recovery mechanisms.

Data Architecture & Modeling

- Design and implement data models, dimensional models, and optimized data structures to support enterprise reporting, analytics, and business intelligence.
- Contribute to enterprise data architecture, solution design, technology evaluation, platform modernization, and technical roadmaps.
- Leverage Databricks and contemporary data architectures to improve data processing efficiency, scalability, performance, and reliability.
- Evaluate appropriate technologies and design patterns based on business requirements, technical feasibility, security standards, and long-term maintainability.

Business Intelligence & Analytics

- Lead the development and optimization of interactive dashboards, scorecards, executive reports, and self-service BI solutions using Power BI and/or Tableau.
- Develop and maintain semantic models, reporting layers, data models,



and reusable analytics components.
- Optimize report performance, data refresh processes, query execution, and overall reporting efficiency.

Data Quality, Governance & Security

- Establish and implement data quality checks, validation rules, reconciliation processes, and monitoring mechanisms.
- Ensure adherence to data governance, metadata management, access control, security, regulatory, and enterprise compliance standards.
- Identify and resolve data inconsistencies, pipeline failures, performance bottlenecks, and production issues.
- Drive continuous improvement initiatives to enhance data reliability, operational efficiency, and solution maintainability.

AI, Advanced Analytics & Modernization

- Support AI, Generative AI, and machine learning initiatives by identifying opportunities for intelligent automation and advanced analytics.
- Contribute to the integration of AI capabilities within data engineering, reporting, and analytics workflows, where applicable.

Technical Leadership & Delivery

- Collaborate with business stakeholders, client leadership, architects, and engineering teams to translate business requirements into scalable technical solutions.
- Own technical delivery across multiple projects and workstreams, ensuring solution quality, performance, timelines, and stakeholder expectations are met.
- Conduct code reviews,



validate technical designs, troubleshoot complex technical issues, and enforce engineering best practices.
- Provide technical guidance on architecture, development standards, performance tuning, deployment methodologies, and production readiness.
- Support solution estimations, proposal development, proof-of-concept (POC) initiatives, and technology assessments as required.

2.

People Management

Responsibilities (20%)

- Mentor and guide team members in data engineering, analytics, business intelligence development, and technical problem-solving.
- Conduct knowledge-sharing sessions and promote continuous learning, technical upskilling, and the adoption of engineering best practices.
- Support individual development plans, career progression, performance feedback, and employee growth opportunities.
- Assist with resource planning, capacity management, work allocation, and utilization tracking across projects.
- Participate in technical interviews, candidate evaluations, recruitment activities, onboarding, and knowledge transfer initiatives.
- Identify skill gaps and support training plans aligned with project requirements and technology roadmaps.
- Monitor team deliverables, commitments, quality standards, and productivity to ensure alignment with project objectives.
- Coordinate priorities across concurrent projects and facilitate the resolution of resource constraints and delivery dependencies.
- Provide performance feedback and support performance management activities in accordance with organizational processes.
- Foster accountability, collaboration, knowledge sharing, and a culture of continuous improvement across teams.

📌 Principal Data Analyst (Chennai)
🏢 Quinte Financial Technologies
📍 Chennai