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

Requirements

• 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

Benefits

• 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