Senior Data Engineer - AWS

Role Overview :

As a Senior Data Engineer, you will be at the heart of our data infrastructure, architecting and maintaining scalable systems that transform raw data into actionable business intelligence. You will work closely with cross-functional teams, including Data Scientists, Product Managers, and Software Engineers, to design robust data pipelines that power our core analytical products.

By ensuring high data availability, quality, and performance, you will directly influence strategic decision-making and drive operational efficiency across the organization. This role is based in our Gurgaon office, where you will collaborate in a high-energy environment dedicated to solving complex data challenges at scale.

Key Responsibilities :

- Design and implement end-to-end data pipelines using AWS services to ensure seamless data ingestion, transformation, and storage for downstream analytics.

- Optimize PySpark jobs and Python-based workflows to improve processing speed and reduce infrastructure costs, directly impacting the efficiency of our data platform.

- Collaborate with stakeholders to translate complex business requirements into scalable technical architectures that support long-term data growth.

- Implement rigorous data quality frameworks and monitoring solutions to maintain high standards of data integrity across all production environments.

- Mentor junior engineers and conduct code reviews to foster a culture of technical excellence and best practices within the data engineering team.

Required Skillset :

- Demonstrated expertise in building and managing large-scale data pipelines within the AWS ecosystem, leveraging services such as S3, Glue, Redshift, and EMR.

- Advanced proficiency in Python and PySpark, with a proven ability to write clean, maintainable, and highly performant code for distributed computing tasks.

- Strong analytical mindset with the ability to communicate complex technical concepts to non-technical stakeholders, ensuring alignment between data initiatives and business goals.

- Proven track record of working effectively in a hybrid or on-site team environment, demonstrating adaptability and a proactive approach to problem-solving.

- A Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field, providing a strong foundation in data structures and system design.

- Minimum 5 to 9 years of hands-on experience in data engineering roles, showcasing a consistent history of delivering high-impact data solutions.

(ref:hirist.tech)