20 days ago
Pune, IndiaSenior
Responsibilities
- Design, develop, and maintain scalable ETL pipelines for large-volume data processing.
- Integrate and unify database systems, APIs, external cloud platforms, and internal data systems.
- Develop and optimize data architectures, transformation technologies, databases, and data warehouses.
- Manage database performance, scalability, and availability.
- Implement monitoring and logging to address data reliability, quality, and processing bottlenecks.
- Apply data governance and security policies.
- Collaborate with data scientists, analysts, business partners, and non-technical stakeholders.
- Coach junior team members.
Requirements
- At least 7.5 years of professional experience.
- 15 years of full-time education.
- Strong experience with data engineering, AWS services, Python, SQL, data warehousing, and data modeling.
- Experience with database management systems, including PostgreSQL and MongoDB, and with NoSQL technologies.
- Experience with Kafka, Hadoop, PySpark, and other big data technologies.
- Experience with data warehousing solutions such as Snowflake, Redshift, and BigQuery.
- Experience with DevOps tools including GitLab, Docker, and Kubernetes.
- Strong analytical and problem-solving skills, with the ability to work independently and collaboratively.
Tech Stack
Amazon RedshiftApache HadoopApache KafkaAWSDockerGoogle BigQueryKubernetesMongoDBPostgreSQLPythonSnowflakeSQL
Categories
Data Engineering
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.