Lead Data Engineer
4 - 7 yrs
₹12L - ₹20L / yr (ESOP available)
Ahmedabad
Skills
Hadoop
Big Data
Data engineering
Spark
Apache Beam
Apache Kafka
Data Warehouse (DWH)
ETL
Python
Java
Scala
C++MySQL
PostgreSQL
MongoDBCassandra
Windows Azure
Amazon Web Services (AWS)Responsibilities:
1. Communicate with the clients and understand their business requirements.
2. Build, train, and manage your own team of junior data engineers.
3. Assemble large, complex data sets that meet the client’s business requirements.
4. Identify, design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources, including the cloud.
6. Assist clients with data-related technical issues and support their data infrastructure requirements.
7. Work with data scientists and analytics experts to strive for greater functionality.
Skills required: (experience with at least most of these)
1. Experience with Big Data tools-Hadoop, Spark, Apache Beam, Kafka etc.
2. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
3. Experience in ETL and Data Warehousing.
4. Experience and firm understanding of relational and non-relational databases like MySQL, MS SQL Server, Postgres, MongoDB, Cassandra etc.
5. Experience with cloud platforms like AWS, GCP and Azure.
6. Experience with workflow management using tools like Apache Airflow.
1. Communicate with the clients and understand their business requirements.
2. Build, train, and manage your own team of junior data engineers.
3. Assemble large, complex data sets that meet the client’s business requirements.
4. Identify, design and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources, including the cloud.
6. Assist clients with data-related technical issues and support their data infrastructure requirements.
7. Work with data scientists and analytics experts to strive for greater functionality.
Skills required: (experience with at least most of these)
1. Experience with Big Data tools-Hadoop, Spark, Apache Beam, Kafka etc.
2. Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
3. Experience in ETL and Data Warehousing.
4. Experience and firm understanding of relational and non-relational databases like MySQL, MS SQL Server, Postgres, MongoDB, Cassandra etc.
5. Experience with cloud platforms like AWS, GCP and Azure.
6. Experience with workflow management using tools like Apache Airflow.
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Companies hiring on Cutshort
About Discite Analytics Private Limited
Founded :
2020
Type :
Products & Services
Size :
20-100
Stage :
Raised funding
About
Discite Analytics & AI is a AI/ML and Data Engineering firm that specializes in creating custom solutions and products for companies of all sizes worldwide. Founded in 2020 by Kunal Singh, a former Uber executive, the company is committed to providing in-depth knowledge of their clients' business and operations to create the best solutions for SMEs.
At Discite Analytics & AI, we invest time interacting with end-users within our clients' companies, not just CXOs, to understand their data requirements fully. We offer a wide range of services, including conducting market research, setting up data pipelines, creating live dashboards, and building machine learning/artificial intelligence solutions to ensure our clients stay ahead of their competition with data-driven decision-making.
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Connect with the team
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Shubham Vishwakarma
Full Stack Developer - AverlonI had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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