Data Engineer

Data Engineering & Architecture

• Design, develop, and maintain scalable, high-performance data pipelines
  

• Work extensively with Azure Data Factory and Microsoft Fabric
  

• Build robust ETL/ELT frameworks using Python
  

• Design and optimize Lakehouse / Data Warehouse architectures
  

• Handle large-scale datasets efficiently (high volume and throughput)
  

• Write and optimize complex SQL queries for performance and reliability
  

• Integrate data from multiple sources including APIs, transactional systems, and external platforms
  

Leadership & Delivery (Hands-on)

• Lead and mentor a team of data engineers while remaining actively involved in coding and solution design
  

• Perform hands-on development for critical pipelines, complex transformations, and performance optimisation.
  

• Conduct code reviews and enforce best practices, design patterns, and coding standards
  

• Act as the technical owner for data engineering deliverables
  

Quality, Performance & Reliability

• Implement data quality checks, validations, and monitoring
  

• Optimize pipelines for performance, scalability, and cost
  

• Ensure reliability, fault tolerance, and error handling in production systems
  

• Follow data security, access control, and compliance best practices
  

• Lead troubleshooting, root-cause analysis, and production issue resolution
  

Collaboration & Continuous Improvement

• Work closely with BI, analytics, product, and business teams
  

• Translate business requirements into scalable technical solutions
  

• Stay up to date with modern data engineering tools, technologies, and techniques
  

• Proactively suggest architectural and process improvement
  

• 3-6 years of experience in the Data Engineering field.
  

• Strong hands-on experience in Python for data engineering, including building and maintaining production-grade, large-scale data pipelines
  

• Advanced experience with Azure Data Factory and Azure-based data platforms for orchestration, integration, and scalable data processing
  

• Working experience with Microsoft Fabric, including Lakehouse and data engineering workloads, along with a strong understanding of ETL/ELT and data warehousing concepts
  

• Expert-level SQL skills covering complex query development, optimization, indexing, and partitioning for high-performance systems
  

• Proven experience handling large-volume, high-throughput data and distributed processing environment.
  

• Experience with analytics and visualization platforms such as Power BI
  

• Knowledge of Delta Lake, Spark, and distributed data processing frameworks
  

• Experience implementing CI/CD practices for data pipelines and data engineering workflows
  

• Exposure to data governance, lineage, metadata management, and compliance-driven environments such as fintech or high-transaction systems
  

• Hands-on leadership mindset with strong ownership and accountability for outcomes
  

• Ability to mentor, guide, and grow junior engineers while leading by example
  

• Clear and effective communication with technical and non-technical stakeholders
  

• Strong problem-solving, analytical reasoning, and decision-making skills
  

• Working hours: 10:00 AM – 7:00 PM
  

• Working days: 5 days a week (plus 1st & 3rd Saturdays working)
  

• Medical Insurance coverage for employees
  

• Provident Fund (PF) facility
  

• Quarterly parties and yearly outings/trips for team bonding
  

• Regular check-ins with leadership for growth and feedback
  

• Recognition awards to celebrate high performance
  

• Fun activities and team engagement sessions throughout the year