Senior Data Engineer
Location: Lahore, Punjab, Pakistan
Senior Data Engineer (12+ Years Experience)
Role Summary
We are seeking a seasoned Senior Data Engineer with 12+ years of experience in designing, building, and managing scalable data pipelines and architectures. The role requires deep expertise in modern data engineering practices, cloud platforms, and enterprise-grade data solutions to support analytics, reporting, and strategic decision-making.
Key Responsibilities
ETL/ELT Development: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
Data Lake & Warehouse Design: Architect and implement scalable data lakes and warehouses to support analytics and BI workloads.
System Optimization: Optimize data processing frameworks for performance, scalability, and cost efficiency.
Data Security: Implement security best practices, encryption, and role-based access controls.
Data Governance: Ensure compliance with governance frameworks, data lineage, and quality standards.
Collaboration: Work closely with data scientists, analysts, and business stakeholders to deliver reliable data solutions.
Automation & CI/CD: Integrate DevOps practices for automated deployment and monitoring of data pipelines.
Mentorship: Provide technical guidance and mentorship to junior engineers, fostering a culture of excellence.
Required Skills
Programming Expertise: Advanced proficiency in Python, Scala, and/or Java for data engineering tasks.
Cloud Platforms: Hands-on experience with AWS, Azure, or GCP for building cloud-native data solutions.
Data Architecture: Strong knowledge of data modeling, warehousing, and distributed systems.
Big Data Tools: Experience with Spark, Hadoop, Kafka, or equivalent frameworks.
SQL Mastery: Expertise in writing optimized queries, stored procedures, and performance tuning.
Visualization Support: Ability to prepare curated datasets for BI tools like Power BI or Tableau.
Problem-Solving: Strong analytical and troubleshooting skills for complex data challenges.
Preferred Qualifications
Experience with containerization (Docker, Kubernetes) for data workloads.
Knowledge of real-time streaming architectures (Kafka, Kinesis, Event Hub).
Familiarity with data mesh and lakehouse architectures.
Exposure to machine learning pipelines and advanced analytics integration.
Proven track record of leading enterprise-scale data engineering projects.
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