Senior Data Engineer

Job Summary We are seeking a highly skilled and hands-on Senior Data Engineer to architect and maintain modern data infrastructure and pipelines. This is a technical role focused on building a scalable data platform that powers analytics, insights, and agentic workflows to enable data-driven decision making across the company. You will work closely with analysts, product, and engineering teams to design end-to-end data solutions using tools like AWS Redshift, Athena, Snowflake, and other leading cloud platforms. Core Responsibilities 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. Optimize data models, queries, and storage strategies for performance, scalability, and cost-effectiveness. Collaborate with cross-functional stakeholders (analytics, product, payments and finance) 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. Develop and maintain infrastructure optimized for both analytics and AI workloads, including transformation and semantic layers. Design and monitor agentic flows aimed at democratizing data access for users across the company, ensuring reliability, scalability, and accuracy. Tech Stack Languages & Tools: Python, SQL Data Warehousing & Query Engines: Snowflake, AWS Redshift, Athena Pipeline & Orchestration: Apache Airflow, AWS Glue, dbt Cloud & DevOps: AWS (Lambda, S3, IAM), Docker, Terraform Streaming: Kafka, Kinesis BI & Analytics: Tableau, Power BI Core Requirements Bachelor's or Master’s degree in Computer Science, Engineering, or related field 5+ years of experience as a Data Engineer, with a strong focus on data pipeline development and data warehousing Deep proficiency in Snowflake or AWS Redshift Strong programming skills in Python and SQL Hands-on experience building LLM-powered applications or workflows in a production environment for analytical use cases, for example ‘ask your data’ interfaces Experience with pipeline orchestration tools (Airflow, Glue, dbt) Solid understanding of data modeling, schema design, and ETL/ELT processes Strong analytical, problem-solving, and communication skills Ability to work cross-functionally and mentor others Experience in high-growth, product-led, or SaaS environments Nice to Have Familiarity with AWS infrastructure and DevOps practices Knowledge of data privacy and security standards (GDPR, SOC2) Solid understanding of agent architectures (tool use, planning, memory management), prompt engineering and evaluation