Lead Data Engineer

• Design and build scalable data pipelines to ingest, process, and store large volumes of structured and unstructured data from diverse sources.
• Develop and maintain robust data warehouse architectures leveraging tools such as AWS Redshift, Athena, and Snowflake.
• Lead and mentor a small team of data engineers, promoting high standards of technical excellence, documentation, and team collaboration.
• Optimize data models, queries, and storage strategies for performance, scalability, and cost-effectiveness.
• Collaborate with cross-functional stakeholders (analytics, product, ML) to gather requirements and deliver data solutions that support business goals.
• Ensure data quality, security, and privacy through best practices in governance, testing, and monitoring.
• Own and operate production data workflows, resolving incidents and ensuring reliability.
• Stay up-to-date with the latest trends and advancements in data engineering and analytics.

• Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or related field.
• 8+ years of experience as a Data Engineer, with a strong focus on data pipeline development and data warehousing.
• Deep proficiency in AWS Redshift, Athena, Snowflake, and experience working with large-scale data systems.
• Strong programming and scripting skills in Python, SQL, and Shell.
• Experience with pipeline orchestration tools (e.g., Airflow, Glue, dbt).
• Solid understanding of data modelling, schema design, and ETL processes.
• Familiarity with cloud infrastructure and DevOps practices (especially AWS).
• Experience with BI platforms like Tableau or Power BI.
• Excellent analytical and problem-solving skills.
• Strong communication, soft skills and leadership skills with the ability to work across functions and mentor others.

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