Engineer/Senior Engineer
24 hours ago
As a Senior Data Engineer at IndiaMart, you will be responsible for designing, implementing, and optimizing data pipelines, ETL processes, and data warehousing solutions. You will collaborate closely with cross-functional teams including product managers, data scientists, analysts, and software engineers to ensure the availability, accuracy, and efficiency of our data ecosystem. The role requires a deep understanding of data engineering best practices, modern data technologies, and a passion for building scalable and robust data systems.
Responsibilities:
- Design, develop, and maintain efficient and scalable data pipelines to support various data initiatives, ensuring the timely delivery of high-quality data to stakeholders.
- Collaborate with data scientists, analysts, and other teams to understand their data requirements and assist in building data solutions that meet those needs.
- Implement ETL processes for extracting, transforming, and loading data from various sources into data warehouses and other storage systems.
- Optimize and fine-tune existing data pipelines for performance and reliability, identifying and resolving bottlenecks and inefficiencies.
- Work with cloud-based technologies (e.g., AWS, Azure, GCP) to build and manage data infrastructure in a cost-effective and secure manner.
- Monitor data pipelines, troubleshoot issues, and implement proactive solutions to ensure data integrity and availability.
- Contribute to the development of data architecture and governance frameworks to maintain data quality, consistency, and security.
- Mentor and provide technical guidance to junior data engineers, fostering skill development and knowledge sharing within the team.
- Stay up-to-date with emerging trends and advancements in data engineering and technology, and evaluate their potential impact on the company's data ecosystem.
Qualifications:
- Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree is a plus.
- Proven experience in data engineering with a focus on designing and implementing complex data pipelines and ETL processes.
- Proficiency in programming languages such as Golang, Python, Java, or similar languages commonly used in data engineering.
- Strong experience with data warehousing solutions (e.g., Redshift, BigQuery) and cloud-based technologies (AWS, Azure, GCP).
- Solid understanding of database technologies, both relational and NoSQL, and experience in query optimization and performance tuning. PostgreSQL knowledge is mandatory.
- Familiarity with data modeling concepts and data architecture best practices.
- Hands-on experience with data pipeline orchestration tools (e.g., Apache Airflow, Apache Kafka, Apache Spark, Debezium) and version control systems (e.g., Git).
- Hands-on experience with deployments of pipelines using Kubernetes.
- Excellent problem-solving skills and the ability to diagnose and resolve complex data engineering issues.
- Strong communication skills, with the ability to collaborate effectively with technical and non-technical stakeholders.
- Prior experience in mentoring or leading junior team members is a plus.
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