Sr. Manager - Data Engineering

Leadsquared is seeking a hands-on result-oriented Senior Manager - Data Engineering to lead and scale our data engineering. This critical leadership role will be responsible for defining and executing the data strategy, building and managing high-performing data engineering teams, and ensuring the availability, quality, and governance of data that fuels our cutting-edge data models and applications. You will partner closely with data Engineers, Data Science, ML Engineering, Product, and other stakeholders to drive innovation and deliver significant business impact through data-driven AI/ML solutionsResponsibilities: * Strategic Leadership: Develop and champion the overall data engineering strategy and roadmap aligned with the companys data lake vision, ML AI objectives and business goals. * Team Building and Management: Recruit, mentor, and lead multiple teams of data engineers, fostering a culture of technical excellence, collaboration, and continuous improvement. * Organizational Scaling: Design and implement the organizational structure and processes necessary to scale the data engineering function to meet the growing demands of our AI/ML initiatives. * AI/ML Data Exposure: Understanding of data requirements for various AI/ML techniques (e.g., supervised learning, unsupervised learning, deep learning, NLP) and design data pipelines accordingly. * Technology Selection: Evaluate and recommend appropriate data technologies and tools (e.g., cloud platforms, data warehouses, data lakes, ETL/ELT tools, streaming platforms, feature stores) based on project requirements and industry best practices. * Pipeline Development: Oversee the development and implementation of scalable and reliable data pipelines using tools like Spark, Flink, Kafka, Airflow, or similar. * Data Quality and Governance: Establish and enforce data quality standards, implement data governance policies, and ensure data security and compliance. * Performance Optimization: Identify and resolve performance bottlenecks in data pipelines and infrastructure to ensure efficient data processing. * Cloud Expertise: Leverage cloud platforms (e.g., AWS,..) and their data services to build and deploy scalable and cost-effective data solutions. * Documentation: Create and maintain comprehensive documentation for data pipelines, data models, and data infrastructure. * Innovation: Stay up-to-date with the latest trends and technologies in data engineering and AI/ML, and proactively propose and implement innovative solutions.Qualifications: * Bachelors or masters degree in computer science, Engineering, or a related field. * 10+ years of experience in data engineering, with a significant focus on building data solutions for applications. * Proven experience leading and mentoring data engineering teams. * Deep understanding of data warehousing concepts, data modelling techniques, and database systems (both SQL and NoSQL). * Strong proficiency in programming languages such as Java, Go, Python and SQL. * Hands-on experience with big data processing frameworks like Spark or Flink. * Experience with ETL/ELT tools and data integration technologies. * Experience with data streaming platforms like Kafka or Kinesis. * Solid understanding of cloud platforms (AWS, Azure, or GCP) and their data engineering services. * Experience with feature stores and feature engineering pipelines is highly desirable. * Knowledge of data governance principles and data quality management. * Excellent problem-solving, analytical, and communication skills. * Ability to work independently and collaboratively in a fast-paced environment.