Highly skilled Lead Data Engineer with extensive experience in ETL development, SQL, database management, Qlik (Qlik Replicate and Qlik Compose), Data Lakes, PySpark, and AWS Glue.

The ideal candidate will lead the design and implementation of scalable data platforms, drive data integration strategies, enable real-time and batch data processing, and ensure high-quality, governed data solutions across enterprise systems.

Key Responsibilities :

- Lead the analysis of multiple data sources and oversee the creation of data mapping documents, data lineage, and transformation logic to ensure transparency, traceability, and governance of data flows.

- Architect, design, and guide the development of scalable ETL pipelines using AWS Glue, PySpark, and SQL, ensuring efficient ingestion and transformation of structured and semi-structured data.

- Lead the adoption of Qlik Compose to automate data warehouse design, streamline schema generation, and accelerate delivery of analytics-ready data models.

- Define and implement robust data integration patterns to load and transform data into Data Lakes (e.g., AWS S3) and downstream analytical platforms.

- Provide technical leadership in database development, including advanced SQL design, data modelling, stored procedures, and performance tuning across Oracle, SQL Server, PostgreSQL, or similar systems.

- Oversee large-scale data processing using PySpark, ensuring optimized distributed data transformations and efficient handling of big data workloads.

- Evaluate, recommend, and implement data architecture and technology strategies aligned with business and scalability requirements.

- Lead root cause analysis and resolution for complex data issues, including discrepancies, latency, and performance bottlenecks.

- Drive continuous improvement in performance, scalability, and cost optimization across AWS Glue jobs, Spark workloads, SQL queries, and Qlik pipelines.

- Mentor and guide junior team members, conduct code reviews, and enforce best practices, reusable frameworks, and development standards.

- Collaborate with cross-functional teams including Data Architects, BI teams, DevOps, and business stakeholders to ensure alignment and efficient delivery of data solutions.

- Ensure adherence to data governance, security, and compliance standards while maintaining system reliability and performance.

Required Skills & Qualifications :

- Strong hands-on and leadership experience in ETL development, advanced SQL, Qlik Replicate and Qlik Compose, PySpark, and AWS Glue.

- Proven experience designing and implementing large-scale data integration and data lake solutions.

- Expertise in relational databases such as Oracle, SQL Server, PostgreSQL, or similar platforms.

- Strong understanding of data modelling, data warehousing concepts, and distributed data processing frameworks.

Preferred Skills :

- Experience with AWS services such as S3, Athena, Redshift, and Lambda.

- Familiarity with workflow orchestration tools such as Airflow, CI/CD pipelines, and data governance and lineage tools.

- Experience working in Agile environments and leading sprint-based delivery.

Key Competencies :

- Strong leadership and mentoring capabilities.

- Excellent problem-solving and analytical thinking.

- Strategic mindset with focus on scalability and optimization.

- Strong communication and stakeholder management skills.