Senior Data Engineer

Job Summary

We are seeking a senior data engineer to design, build, and maintain production-grade data pipelines and lakehouse solutions in an on-premises environment, while driving data platform initiatives, performance, security, and technical best practices.

Mandatory Skill Set

• 8+ years of IT experience with 5+ years in data engineering/data pipelines
• Expert SQL/SQL Server - query optimization, indexing & performance tuning
• Advanced Python & PySpark
• Apache Spark and distributed data processing
• Kubernetes & Docker for on-premises deployments
• Data modelling - relational & NoSQL hands-on MongoDB/Cassandra
• Lakehouse/Data Lake architecture, including Iceberg, partitioning & metadata
• ETL/ELT orchestration - Apache Airflow or similar
• CI/CD, Git, automated testing & IaC
• Data security, governance, RBAC, masking & compliance.

Desired Skill Set

• Experience in data virtualization, logical data warehouses, Data Mesh/Fabric architectures, metadata management, and data lineage
• Familiarity with real-time streaming technologies such as Kafka/Flink, along with experience in technical leadership, mentoring, and Agile data architecture.

Responsibilities

• Design and develop production-grade ETL/ELT pipelines using Python/PySpark
• Build and manage multi-layer lakehouse architecture across raw, curated, and consumption layers
• Deploy scalable data pipelines using Kubernetes/Docker in on-premise environments
• Develop data models and optimize complex SQL Server queries and performance
• Establish CI/CD, automated testing, monitoring, and version-control practices
• Implement data security, governance, and access controls
• Mentor engineers, conduct code reviews, and drive engineering best practices
• Collaborate with data scientists, BAs, and stakeholders to deliver business-ready datasets
• Provide L3 support and lead resolution of complex data engineering challenges.

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