Cloud Big Data Engineer

1 week ago


Pune, India IT Full time

We are hiring Cloud Big Data Engineer.

Location : Experience level : 5+ years.

Required Skills : GCP, BigData, Pyspark, Python, Spark, Kafka, Hadoop, Hive, Scala/Django, DFS Elastic search.

Key Responsibilities :


- Design, develop, and implement big data solutions on the Google Cloud Platform (GCP).


- Develop and maintain data pipelines for data ingestion, transformation, and loading into data warehouses and data lakes.


- Work with Apache Spark, Hadoop (HDFS, Hive), and other big data technologies to process and analyze large datasets.


- Develop and deploy data pipelines using tools like Apache Kafka.


- Utilize NoSQL databases such as ElasticSearch for data storage and retrieval.


- Develop and maintain data quality checks and ensure data integrity.


- Collaborate with data analysts, data scientists, and other stakeholders to understand business requirements and translate them into technical solutions.


- Optimize data pipelines for performance and scalability.


- Troubleshoot and resolve data-related issues.


- Stay up-to-date with the latest advancements in big data technologies and cloud :


Education : Bachelor's degree in Computer Science, Engineering, or a related field.


Experience : 5+ years of experience in big data engineering, data warehousing, or a related field.


Technical Skills :


- Strong proficiency in Python and experience with frameworks like Django.


- In-depth knowledge of Apache Spark, Hadoop (HDFS, Hive), and other big data technologies.


- Experience with data ingestion, transformation, and loading tools.


- Experience with NoSQL databases, particularly ElasticSearch.


- Experience with cloud platforms, preferably GCP.


- Proficiency in Linux/Unix and shell scripting.


Preferred Skills :


- Experience with data streaming platforms like Kafka.


- Experience with data visualization and reporting tools (e.g., Tableau, Power BI).


- Experience with containerization technologies (Docker, Kubernetes).


- Knowledge of distributed systems concepts (load balancing, sharding, data distribution).


- Cloud certifications (e.g., Google Cloud Certified Professional Data Engineer)

(ref:hirist.tech)
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