ACI Hiring Drive 2024: ACI Hiring Drive 2024 for its Cloud Data Engineer. ACI Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Bachelor s degree. if you are interested, please apply as soon as possible.
Company Name: ACI
Role: Cloud Data Engineer
Location: Hyderabad, Bengaluru
Experience: 0 to 5 years
Qualification: Bachelor s degree
Batch: Any
Job Type: Full Time
Salary: Best in Industry
ACI Hiring Drive 2024
Job Description:
- We have a new urgent open position for Cloud Data Engineer.
- Below you can find the Key responsibilities and Required Skills and Experience.
- The Cloud Data engineer should have experience in Python Coding and should have exposure to AWS or Azure and have experience in writing serverless code.
Requirements:
- Strong expertise in advanced data modeling, schema and ETL process design, implementation, and maintenance
- Experience with numerous data lake / warehouse technologies (Databricks, Snowflake, Presto, Dremio)
- Strong background in advanced SQL and focused on understanding, manipulating, processing and extracting values from large datasets and data streams
- Experience with different variety of data types (JSON, Parquet, Excel, Flat files)
- Experience with databases and data storage frameworks including: Azure SQL, Postgresql, Elasticsearch, Mongo, Cosmos DB, Delta Lake
- Expertise in cloud messaging platforms including Apache Kafka or Azure Service Bus
Responsibility:
- Develop and support scalable, extensible, and highly available data pipelines on heterogeneous datasets that power downstream applications and systems and serve content to our web and API products
- Closely collaborate with partners across product and design, engineering, and business teams to drive innovations that improve our customers experience
- Follow software-development best practices including test-driven development, contributing to documentation, feature flagging, etc
- Help to maintain and improve existing ETL pipelines
- work with your team to troubleshoot and fix issues in ingest and processing, considering dependencies and integration points
- Collaborate with DevOps to plan resources and continuously optimize the infrastructure and configuration of our data pipelines to ensure a healthy and high-performance production deployments
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