Role Overview :

We are seeking a seasoned AWS Data Engineer to join our high-impact data platform team in Pune or Chennai. In this role, you will architect, build, and maintain scalable data pipelines that serve as the backbone for our analytical and machine learning initiatives.

You will collaborate closely with cross-functional teams, including data scientists, product managers, and business stakeholders, to transform complex raw data into actionable insights. By designing robust data architectures and optimizing cloud-native workflows, you will directly influence our ability to make data-driven decisions, ultimately enhancing customer experiences and driving operational efficiency across the organization.

Key Responsibilities :

- Architect and implement end-to-end ETL/ELT pipelines on AWS to ensure seamless data ingestion, transformation, and delivery for downstream consumption.

- Design and maintain high-performance data warehouse solutions that support complex analytical queries and business intelligence reporting.

- Develop and optimize data models to ensure data integrity, scalability, and performance across distributed systems.

- Collaborate with engineering teams to automate data workflows using Python and PySpark, reducing manual intervention and improving system reliability.

- Partner with stakeholders to translate business requirements into technical data specifications, ensuring alignment between data infrastructure and organizational goals.

Required Skillset :

- Demonstrated expertise in designing and managing large-scale data ecosystems within the AWS cloud environment, leveraging services such as S3, Redshift, Glue, and EMR.

- Proficiency in writing production-grade Python code and building complex data processing jobs using PySpark to handle high-volume datasets.

- Strong command of data modeling techniques and database design principles, with the ability to structure data for both transactional and analytical workloads.

- Proven ability to communicate technical concepts clearly to non-technical stakeholders, fostering a collaborative environment across distributed teams.

- A minimum of 5 to 13 years of professional experience in data engineering, with a track record of delivering robust, scalable solutions in a fast-paced, hybrid work environment.

- A degree in Computer Science, Engineering, or a related quantitative field, complemented by a proactive mindset toward learning new cloud technologies and industry best practices.