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Data Engineer(AWS+PYSPARK+SQL)

Data Engineer(AWS+PYSPARK+SQL) at ProtoGene Consulting Private Limited · Mumbai · 3 - 8 years · ₹7L - ₹18L / yr · Bootstrapped · Posted 18 Dec 2024

ProtoGene Consulting Private Limited's logo

Data Engineer(AWS+PYSPARK+SQL)

Anand Singh's profile picture
Posted by Anand Singh
3 - 8 yrs
₹7L - ₹18L / yr
Mumbai
Skills
PySpark
Data engineering
Big Data
Hadoop
Spark
skill iconAmazon Web Services (AWS)
SQL
AWS GLUE
Apache Airflow

Data Engineer + Integration engineer + Support specialistExp – 5-8 years

Necessary Skills:· SQL & Python / PySpark

· AWS Services: Glue, Appflow, Redshift

· Data warehousing

· Data modelling

Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform. Design/ implement, and maintain the data architecture for all AWS data services

· A strong understanding of data modelling, data structures, databases (Redshift), and ETL processes

· Work with stakeholders to identify business needs and requirements for data-related projects

Strong SQL and/or Python or PySpark knowledge

· Creating data models that can be used to extract information from various sources & store it in a usable format

· Optimize data models for performance and efficiency

· Write SQL queries to support data analysis and reporting

· Monitor and troubleshoot data pipelines

· Collaborate with software engineers to design and implement data-driven features

· Perform root cause analysis on data issues

· Maintain documentation of the data architecture and ETL processes

· Identifying opportunities to improve performance by improving database structure or indexing methods

· Maintaining existing applications by updating existing code or adding new features to meet new requirements

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Recommending infrastructure changes to improve capacity or performance

Experience in Process industry

Data Engineer + Integration engineer + Support specialistExp – 3-5 years

Necessary Skills:· SQL & Python / PySpark

· AWS Services: Glue, Appflow, Redshift

· Data warehousing basics

· Data modelling basics

Job Description:· Experience of implementing and delivering data solutions and pipelines on AWS Cloud Platform.

· A strong understanding of data modelling, data structures, databases (Redshift)

Strong SQL and/or Python or PySpark knowledge

· Design and implement ETL processes to load data into the data warehouse

· Creating data models that can be used to extract information from various sources & store it in a usable format

· Optimize data models for performance and efficiency

· Write SQL queries to support data analysis and reporting

· Collaborate with team to design and implement data-driven features

· Monitor and troubleshoot data pipelines

· Perform root cause analysis on data issues

· Maintain documentation of the data architecture and ETL processes

· Maintaining existing applications by updating existing code or adding new features to meet new requirements

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Identifying opportunities to improve performance by improving database structure or indexing methods

· Designing and implementing security measures to protect data from unauthorized access or misuse

· Recommending infrastructure changes to improve capacity or performance


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About ProtoGene Consulting Private Limited

Founded :
2018
Type :
Services
Size :
0-20
Stage :
Bootstrapped

About

Enabling organizations to utilize the power of technology to transform the data asset into knowledge to execute. ProtoGene provides consulting and services to organizations for • Advanced Analytics & Predictive Modeling • Data Visualization • Data Management • Data Governance
Read more

Connect with the team

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Tarun Soni

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I 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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