
Search by job, company or skills
Role Overview
The Lead Data Engineer will be responsible for designing, developing, and delivering high-quality software and data solutions while leading a team of engineers. The role involves hands-on technical work, architectural decision-making, mentoring junior developers, and collaborating with cross-functional teams to ensure successful delivery of scalable data platforms and analytical solutions.
Key Responsibilities
· Lead the end-to-end design, development, and delivery of software systems, data pipelines, and components.
· Define technical strategy, architecture, and best practices for development and data engineering.
· Design and build optimized data pipelines using cutting-edge technologies in a cloud environment.
· Construct infrastructure for efficient ETL processes from various sources and storage systems.
· Architect, design, and maintain database pipeline architectures, ensuring readiness for AI/ML transformations.
· Lead the implementation of algorithms and prototypes to transform raw data into useful information.
· Review code for quality, scalability, and performance.
· Collaborate with Product Managers, Business Managers, Designers, and QA teams to translate business requirements into technical solutions.
· Develop analytical tools, programs, and reporting mechanisms.
· Create data validation methods and data analysis tools.
· Interpret data trends and patterns to establish operational alerts.
· Conduct complex data analysis and present results effectively.
· Prepare data for prescriptive and predictive modeling.
· Ensure compliance with data governance and security policies.
· Troubleshoot, debug, and resolve complex technical issues.
· Drive continuous improvement in software and data development processes, tools, and methodologies.
· Mentor and guide engineers through code reviews, technical discussions, and training.
· Ensure timely delivery of projects while maintaining high engineering standards.
· Continuously explore opportunities to enhance data quality and reliability.
· Apply strong programming and problem-solving skills to develop scalable solutions.
· Demonstrate passion for testing strategy, problem-solving, and continuous learning.
· Willingness to acquire new skills and knowledge.
· Possess a product/engineering mindset to drive impactful data solutions.
· Experience working in distributed environments with global teams.
· Stay current with emerging technologies and industry trends to propose innovative solutions.
Technical Skills and Experience Requirements
· Minimum 8+ years of hands-on experience designing, building, deploying, testing, maintaining, monitoring, and owning scalable, resilient, and distributed data pipelines.
· High proficiency in Python, Scala, and Spark for applied large-scale data processing.
· Expertise with big data technologies, including Spark, Data Lake, Delta Lake, and Hive.
· Solid understanding of batch and streaming data processing techniques.
· Proficient knowledge of the Data Lifecycle Management process, including data collection, access, use, storage, transfer, and deletion.
· Expert-level ability to write complex, optimized SQL queries across extensive data volumes.
· Experience with RDBMS and OLAP databases such as MySQL and Snowflake.
· Familiarity with Agile methodologies.
· Obsession for service observability, instrumentation, monitoring, and alerting.
· Knowledge or experience in architectural best practices for building data lakes.
Qualifications
· Bachelor's degree in computer science, Engineering, Information Systems, or related field
· Relevant Experience: 8+ Years (as Python and Data Engineer)
· Overall IT Experience: 8–12 Years
Job ID: 152995915