Lead Data Engineer

Duties & Responsibilities Lead the design, development, and optimization of ETL/ELT pipelines and workflows Write, tune, and optimize advanced SQL queries for large-scale data processing Build and maintain data warehouses and data models (relational, dimensional, star schema) Translate business requirements into robust, well-architected, and reusable data solutions Partner with analysts, data scientists, and stakeholders to deliver trusted, actionable datasets Implement and maintain unit tests, integration tests, and validation frameworks to ensure pipeline reliability Document workflows, and design decisions to support knowledge sharing and operational continuity Apply coding standards, CI/CD practices, version control, and peer code reviews to ensure high-quality deliverables Proactively monitor, optimize, and troubleshoot pipelines for performance, scalability, and cost efficiency Support deployments and handle post-production monitoring and incident resolution Mentor associate engineers, providing technical guidance and feedback Requirements Basic Qualifications Bachelor’s degree in computer science, Information Systems, Engineering, or a related field 6-10 years of hands-on experience in data engineering or related fields Expertise in writing complex SQL queries, optimizing, using advanced functionals and turning the performance on cloud data warehouse environment. Strong experience with data warehousing concepts, design, and implementation Minimum 6 years of hands-on experience with Snowflake or modern cloud data warehouse Minimum 3 years of hands-on experience in data modeling Minimum 2 year of hands-on Python development (ETL/ELT scripting, OOP, automation) Strong knowledge of at least one major cloud platform (AWS, Azure, or GCP) Experience with orchestration tools (e.g., Airflow, ADF, Luigi) for workflow management Demonstrated ability to lead and mentor teams while managing multiple priorities Strong communication and stakeholder management skills Strong hands-on experience with data warehousing concepts, design, and implementation Preferred Qualifications Hands-on experience with DBT (Data Build Tool) for data transformations Familiarity with DevOps and CI/CD best practices in data engineering Exposure with real-time/streaming platforms (Kafka, Spark Streaming, Flink) Exposure to the e-commerce domain or large-scale B2B/B2C environments Has the ability to break down problems and estimate time for development tasks Experience mentoring and guiding junior engineers Understands the technology landscape, up to date on current technology trends and new technology, brings new ideas to the team Learns organization vision statement and decision-making framework. Able to understand how team and personal goals/objectives contribute to the organization vision