- Senior
Prodapt is the largest specialized player in the Connectedness industry. As an AI-first strategic technology partner, we serve telecom and tech companies that are building networks and shaping the digital experiences of tomorrow. We deliver consulting, managed services, and business reengineering. Our strength comes from being both AI-first and Telco-native. Gartner recognizes Prodapt as a Large, Telecom-Native Regional IT Service Provider. This expertise allows us to provide tailored solutions that directly address industry challenges. Our focus is on being a customer-centric partner, fully aligning with our client's business goals and driving their success at every step. With over 6,000 Prodaptians across 30+ countries and backed by the 130-year legacy of the Jhaver Group, Prodapt combines a heritage of excellence with cutting-edge innovation.
As a Senior Data Engineer, you will be responsible for designing, building, and maintaining the data infrastructure and pipelines that fuel our data-driven decision-making. You will work closely with data scientists, analysts, and other engineers to ensure data is readily available, reliable, and optimized for various use cases.
Responsibilities:- Design, build, and maintain scalable and robust data pipelines using a variety of tools and technologies.
- Develop and implement data ingestion and processing frameworks for both batch and real-time data streams.
- Optimize data pipelines for performance, scalability, and cost-effectiveness.
- Implement data quality checks and monitoring to ensure data accuracy and integrity.
- Design and implement data warehouse solutions to support analytical and reporting needs.
- Develop and maintain data models that are optimized for query performance and data integrity.
- Implement data governance policies and procedures to ensure data quality and compliance.
- Design and implement data solutions on cloud platforms (e.g., AWS, Azure, GCP).
- Utilize cloud-native services for data storage, processing, and analysis.
- Manage and optimize cloud infrastructure for data-intensive applications.
- Collaborate effectively with data scientists, analysts, and other engineers to understand data needs and requirements.
- Communicate technical concepts and solutions clearly and concisely to both technical and non-technical audiences.
- Contribute to the development and implementation of data engineering best practices.
- Stay up-to-date with the latest technologies and trends in data engineering.
- Bachelor's or master’s degree in computer science, Engineering, or a related field.
- 5+ years of experience in data engineering or a related role.
- Strong understanding of data warehousing concepts and techniques.
- Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL, Oracle).
- Experience with big data technologies such as Hadoop, Spark, Hive, Hadoop orchestration engine, Oozie
Teradata, ESPX and Kafka.
- Experience with data pipeline orchestration tools (e.g., Airflow).
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
