Job
Description
We are seeking a seasoned Data Engineering Manager with 8+ years of experience to lead and grow our data engineering capabilities. This role demands strong hands-on expertise in Python, SQL, Spark , and advanced proficiency in AWS and Databricks . As a technical leader, you will be responsible for architecting and optimizing scalable data solutions that enable analytics, data science, and business intelligence across the organization. Key Responsibilities: Lead the design, development, and optimization of scalable and secure data pipelines using AWS services such as Glue, S3, Lambda, EMR , and Databricks Notebooks , Jobs, and Workflows. Oversee the development and maintenance of data lakes on AWS Databricks , ensuring performance and scalability. Build and manage robust ETL/ELT workflows using Python and SQL , handling both structured and semi-structured data. Implement distributed data processing solutions using Apache Spark / PySpark for large-scale data transformation. Collaborate with cross-functional teams including data scientists, analysts, and product managers to ensure data is accurate, accessible, and well-structured. Enforce best practices for data quality, governance, security , and compliance across the entire data ecosystem. Monitor system performance, troubleshoot issues, and drive continuous improvements in data infrastructure. Conduct code reviews, define coding standards, and promote engineering excellence across the team. Mentor and guide junior data engineers, fostering a culture of technical growth and innovation. Requirements 8+ years of experience in data engineering with proven leadership in managing data projects and teams. Expertise in Python, SQL, Spark (PySpark) ,
