Job Title: Principal Data Engineer Location: Lahore/Karachi/Islamabad Job Type: Full-time Company Overview   10Pearls is an award-winning end-to-end digital innovation company that helps businesses imagine and build the future. We are proud to announce that 10Pearls was named as winner of the Best Tech Work Culture Timmy Award in Washington DC by Tech in Motion, recognized on the Inc. 5000 Fastest-Growing Companies List, and was ranked the #1 Most Diverse Midsize Company in Greater Washington. We partner with businesses to help them transform, scale, and accelerate by adopting digital and exponential technologies. Our work has ranged from creating highly usable, secure digital experiences, mobile and software products, to helping businesses modernize through cloud adoption and development and the digitalization of their business processes. Our clientele is highly diverse, including Global 1000 enterprises, mid-market businesses, and even high-growth start-ups. But those are just facts. What makes us unique is that we have a true heart and soul. We have a strong focus on a double bottom line and actively support and engage with the communities where we live and work to make the world a better place. In a nutshell, we believe in doing well, while doing good and know how to balance the two.   Role 10Pearls is seeking a Senior Principal Data Engineer with strong expertise in modern data platforms, cloud technologies, and large-scale data processing. The ideal candidate will be responsible for designing, developing, and maintaining scalable batch and real-time data solutions, enabling data-driven decision-making across the organization while ensuring data quality, governance, and operational excellence. Responsibilities - Design, develop, and maintain scalable batch and real-time data pipelines to support growing data volume and complexity - Build and optimize data solutions on cloud-based and on-premises data platforms (Azure, AWS, Google Cloud) - Develop data models, data marts, and data domains including laying the foundation for Data Mesh architecture - Implement and maintain ETL/ELT processes for efficient data integration and transformation - Collaborate with data analysts, data scientists, and business stakeholders to deliver reliable data solutions - Ensure data quality, governance, security, and compliance across the full data ecosystem including access controls, data masking, and encryption - Automate deployment, scheduling, monitoring, and management of data pipelines and datasets - Monitor platform performance and troubleshoot data-related issues while providing L2/L3 production support - Develop and maintain data orchestration frameworks and DataOps best practices - Optimize existing data infrastructure and recommend improvements for scalability and performance; identify potential bottlenecks proactively - Participate in architecture discussions and contribute to data strategy and roadmap initiatives - Implement disaster recovery, business continuity, and risk management controls for data platforms - Support audit, compliance, and regulatory requirements related to data management - Collaborate with the Incident Management team to track, resolve, and report on data platform incidents and follow-up actions - Identify KPIs for data engineering deliverables in alignment with business requirements - Collaborate with cross-functional teams to ensure successful project delivery and production deployments - Maintain technical documentation, standards, and best practices across data engineering initiatives Requirements - Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field - Minimum 7+ years of experience in Data Engineering and large-scale data platforms - Strong expertise in Big Data technologies including Hadoop, Spark (including Spark Streaming), Kafka, Hive, Airflow, and Apache NiFi - Advanced proficiency in Python and SQL - Hands-on experience with Azure Data Platform services including Azure Data Factory (ADF), Azure Databricks, Azure Data Lake Storage (ADLS), Azure Synapse Analytics, Azure Functions, and Logic Apps; or equivalent data stack knowledge within Google Cloud or AWS Cloud - Hands-on experience with Google BigQuery, Google Analytics, and Clickstream data modelling - Strong experience in building and maintaining ETL/ELT pipelines - Proficiency in relational SQL, Graph, NoSQL, and distributed database technologies - Proficiency in Elasticsearch and Couchbase databases - Expertise in data modeling techniques including Star Schema, 3NF, and Data Vault - Experience with workflow orchestration tools including Airflow, Oozie, and CI/CD tools - Knowledge of real-time data streaming platforms such as Kafka - Experience with Power BI, Tableau, Qlik, or similar reporting and visualization tools - Strong understanding of Data Governance, Data Architecture, Data Security, and Data Management principles - Experience with cloud-based data migration and modernization initiatives including hybrid on-premises and cloud architectures - Strong analytical, troubleshooting, and problem-solving skills - Excellent communication and stakeholder management abilities Nice to Have - Exposure to AI, Machine Learning, and Advanced Analytics platforms - Financial Services domain experience - Knowledge of Agile and Waterfall delivery methodologies - Program Management and deliverable tracking experience - Experience leading technical teams and mentoring junior engineers