Data Engineer Lead

As a Data Engineer Lead with 57 years of experience, your role will involve designing, building, and optimizing scalable data platforms and pipelines. You will take full ownership of data engineering initiatives, ensuring high-quality data delivery, and collaborating with cross-functional teams to drive data strategy and innovation. Key Responsibilities: - Lead the design, development, and maintenance of scalable, secure, and automated data pipelines (batch and streaming). - Build, optimize, and manage data lakes / data warehouses on platforms such as Redshift, Snowflake, BigQuery, or Delta Lake. - Develop and deploy data workflows using Airflow, DBT, Spark, Kafka, and other modern data engineering tools. - Implement and optimize ETL/ELT processes, ensuring data quality, governance, lineage, and observability. - Define data strategy, architecture, and KPIs in collaboration with analytics, product, and engineering teams. - Mentor junior and mid-level data engineers, ensuring adherence to best practices and coding standards. - Build and maintain CI/CD pipelines for data engineering processes using tools like GitHub Actions, Jenkins, or similar. - Deploy and manage container environments using Docker and Kubernetes. - Ensure performance optimization of queries, storage, pipelines, and cloud infrastructure. - Drive innovation by evaluating new tools, technologies, and architectural improvements. Required Skills & Qualifications: Core Technical Skills: - Strong expertise in data processing & workflow automation. - Expert-level proficiency in Python and SQL. - Hands-on experience with Cloud Platforms (AWS / GCP / Azure) for data engineering services. - Proven experience building and managing pipelines using Airflow, DBT, Spark, Kafka, etc. - Strong understanding of modern data warehousing technologies: Redshift, Snowflake, BigQuery, Delta Lake. - Experience with CI/CD tools (GitHub Actions, Jenkins, Bitbucket Pipelines, etc.). - Strong working knowledge of Docker, Kubernetes, and containerized deployments. Preferred Skills: - Knowledge of data governance, lineage, metadata management, and observability frameworks. - Experience with distributed systems and performance tuning. - Familiarity with version control (Git), DevOps practices, and cloud cost optimization. Soft Skills: - Strong leadership and mentoring capabilities. - Excellent communication and stakeholder management skills. - Analytical mindset with a strong problem-solving approach. - Ability to work in a fast-paced, data-driven environment.,