Description :

Role Overview :

The Python Developer (Data Engineer) will be responsible for designing, developing, and optimizing scalable data delivery solutions on AWS-based data warehouse platforms.

The role focuses on building robust ETL pipelines, integrating multiple data sources, and enabling high-quality data consumption for analytical dashboards and business intelligence reports. These insights will support strategic decision-making across business teams, including market trend analysis and performance optimization.

Mandatory Skills :

- Python (advanced scripting and data processing)

- SQL (complex queries, performance tuning, stored procedures)

- AWS Services: Redshift, S3, EC2, API Gateway

- Version Control: Git

- CI/CD pipelines and automation

Key Responsibilities :

- Design, develop, and maintain scalable ETL and ELT pipelines for data ingestion, transformation, and delivery on AWS-based data warehouse platforms.

- Collaborate with Product Owners, Data Analysts, Developers, and AWS Infrastructure teams to understand business requirements and translate them into efficient data solutions.

- Build and optimize data models to support analytics, reporting, and dashboarding use cases.

- Develop and optimize SQL queries, views, and stored procedures to ensure high-performance data access.

- Implement and manage data ingestion processes from multiple structured and semi-structured sources using AWS services such as S3, Glue, DMS, Data Pipeline, and Lambda.

- Design and develop API integrations using AWS API Gateway and backend services for real-time or near-real-time data access.

- Ensure data quality, integrity, and consistency across the data warehouse and downstream reporting systems.

- Automate data workflows, deployments, and monitoring using CI/CD pipelines and scripting.

- Apply best practices in data security, access control, and compliance within AWS environments.

- Troubleshoot data pipeline failures, performance bottlenecks, and production issues, proposing and implementing long-term solutions.

- Adhere to established analytics standards, governance frameworks, and data engineering best practices.

- Actively participate in Agile/Scrum ceremonies, including sprint planning, stand-ups, reviews, and retrospectives.

- Continuously evaluate and adopt new tools, technologies, and frameworks to improve data engineering efficiency and scalability.

Technical Requirements :

- Strong experience in data architecture, including data modeling, data mining, and large-scale data ingestion.

- Hands-on experience with AWS ecosystem components such as S3, Glue, Data Pipeline, DMS, RDS, Redshift, Lambda, and EC2.

- Expertise in building ETL frameworks using Python, SQL, and optionally Node.js.

- Solid understanding of data warehousing concepts, dimensional modeling, and big data processing.

- Experience working with relational databases such as SQL Server and PostgreSQL.

- Familiarity with CI/CD tools for automated build, test, and deployment of data pipelines.

- Strong understanding of Git-based version control and collaborative development workflows.

Soft Skills & Competencies :

- Strong analytical and problem-solving skills with the ability to propose scalable and efficient solutions.

- Excellent communication skills to interact effectively with both technical and business stakeholders.

- Ability to work independently as well as collaboratively within cross-functional Agile teams.

- High adaptability and eagerness to learn new technologies and frameworks in a fast-paced environment.

- Strong ownership mindset with attention to detail and data accuracy.

Education Qualification :

- Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or a related field.

Preferred Qualifications :

- Experience supporting BI tools and visualization platforms.

- Exposure to data governance, metadata management, and data quality frameworks.

- Prior experience in media, entertainment, or analytics-driven business domains is an advantage.