Engineering Manager Data Engineering

Job Description Engineering Manager (Databricks / Data Engineering) Job Title Engineering Manager Databricks / Data Engineering Job Summary We are seeking an experienced Engineering Manager to lead a team of Data Engineers in designing, developing, and delivering scalable data platforms on Databricks. The role involves driving technical excellence, people leadership, delivery management, stakeholder engagement, and continuous improvement while ensuring high-quality, secure, and reliable data solutions. Key Responsibilities Technical Leadership Lead the design and implementation of scalable data platforms using Databricks. Define technical architecture, coding standards, and engineering best practices. Drive adoption of modern data engineering patterns including Medallion Architecture. Review solution designs, code, and performance optimization strategies. Ensure data security, governance, and compliance standards are followed. Delivery Management Own end-to-end delivery of multiple data engineering initiatives. Plan sprint execution and manage project timelines. Identify and mitigate delivery risks and dependencies. Ensure production readiness and successful release management. Drive continuous improvement in engineering processes. People Management Lead and mentor a team of Data Engineers and Technical Leads. Conduct performance reviews and career development discussions. Support hiring, onboarding, and capability development. Foster a culture of collaboration, innovation, and accountability. Stakeholder Management Collaborate with Product Owners, Architects, Business stakeholders, and Platform teams. Communicate delivery progress, risks, and technical decisions. Manage stakeholder expectations and prioritize business requirements. Operational Excellence Ensure platform reliability, availability, and performance. Drive root cause analysis for production incidents. Improve monitoring, alerting, and observability. Optimize cloud infrastructure and operational costs. Required Skills Databricks Databricks Workspace Delta Lake Delta Live Tables (DLT) Unity Catalog Databricks Workflows Auto Loader Structured Streaming MLflow (preferred) Photon Engine Databricks Asset Bundles (preferred) AI Skills Nice to Have Genie & Cursor AI Cloud Platforms Microsoft Azure AWS or Google Cloud Platform Cloud Storage (ADLS, S3, GCS) Data Engineering Apache Spark (PySpark and Spark SQL) Python SQL Data Warehousing ETL/ELT Design Medallion Architecture Batch and Streaming Data Pipelines Data Modeling (Star, Snowflake, Data Vault) DevOps & CI/CD Git Azure DevOps / GitHub CI/CD Pipelines Terraform (preferred) Infrastructure as Code Database Technologies SQL Server Oracle Snowflake PostgreSQL NoSQL databases (preferred) Leadership Skills Engineering leadership Team management Agile delivery Stakeholder management Risk management Conflict resolution Coaching and mentoring Resource planning Budget and capacity planning Preferred Experience 10 15+ years of experience in Data Engineering. 3 5+ years of experience leading engineering teams. Hands-on experience with Databricks on Azure, AWS, or GCP. Experience building enterprise-scale data platforms. Strong understanding of cloud-native architectures and data governance. Experience with performance tuning, cost optimization, and production support. Nice to Have Databricks Certified Data Engineer Professional Azure Data Engineer Associate Azure Solutions Architect Experience with Apache Kafka or Event Hubs Knowledge of AI/ML pipelines and Generative AI Experience with Data Mesh or Data Fabric architectures Job Description Engineering Manager (Databricks / Data Engineering) Job Title Engineering Manager Databricks / Data Engineering Job Summary We are seeking an experienced Engineering Manager to lead a team of Data Engineers in designing, developing, and delivering scalable data platforms on Databricks. The role involves driving technical excellence, people leadership, delivery management, stakeholder engagement, and continuous improvement while ensuring high-quality, secure, and reliable data solutions. Key Responsibilities Technical Leadership Lead the design and implementation of scalable data platforms using Databricks. Define technical architecture, coding standards, and engineering best practices. Drive adoption of modern data engineering patterns including Medallion Architecture. Review solution designs, code, and performance optimization strategies. Ensure data security, governance, and compliance standards are followed. Delivery Management Own end-to-end delivery of multiple data engineering initiatives. Plan sprint execution and manage project timelines. Identify and mitigate delivery risks and dependencies. Ensure production readiness and successful release management. Drive continuous improvement in engineering processes. People Management Lead and mentor a team of Data Engineers and Technical Leads. Conduct performance reviews and career development discussions. Support hiring, onboarding, and capability development. Foster a culture of collaboration, innovation, and accountability. Stakeholder Management Collaborate with Product Owners, Architects, Business stakeholders, and Platform teams. Communicate delivery progress, risks, and technical decisions. Manage stakeholder expectations and prioritize business requirements. Operational Excellence Ensure platform reliability, availability, and performance. Drive root cause analysis for production incidents. Improve monitoring, alerting, and observability. Optimize cloud infrastructure and operational costs. Required Skills Databricks Databricks Workspace Delta Lake Delta Live Tables (DLT) Unity Catalog Databricks Workflows Auto Loader Structured Streaming MLflow (preferred) Photon Engine Databricks Asset Bundles (preferred) AI Skills Nice to Have Genie & Cursor AI Cloud Platforms Microsoft Azure AWS or Google Cloud Platform Cloud Storage (ADLS, S3, GCS) Data Engineering Apache Spark (PySpark and Spark SQL) Python SQL Data Warehousing ETL/ELT Design Medallion Architecture Batch and Streaming Data Pipelines Data Modeling (Star, Snowflake, Data Vault) DevOps & CI/CD Git Azure DevOps / GitHub CI/CD Pipelines Terraform (preferred) Infrastructure as Code Database Technologies SQL Server Oracle Snowflake PostgreSQL NoSQL databases (preferred) Leadership Skills Engineering leadership Team management Agile delivery Stakeholder management Risk management Conflict resolution Coaching and mentoring Resource planning Budget and capacity planning Preferred Experience 10 15+ years of experience in Data Engineering. 3 5+ years of experience leading engineering teams. Hands-on experience with Databricks on Azure, AWS, or GCP. Experience building enterprise-scale data platforms. Strong understanding of cloud-native architectures and data governance. Experience with performance tuning, cost optimization, and production support. Nice to Have Databricks Certified Data Engineer Professional Azure Data Engineer Associate Azure Solutions Architect Experience with Apache Kafka or Event Hubs Knowledge of AI/ML pipelines and Generative AI Experience with Data Mesh or Data Fabric architectures Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.