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Aws Data Engineer @ Celebal Technologies

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 Aws Data Engineer

Job Description

Overview:

As a Data Engineer, you will work with multiple teams to deliver solutions on the AWS Cloud using core cloud data engineering tools such as Databricks on AWS, AWS Glue, Amazon Redshift, Athena, and other Big Data-related technologies. This role focuses on building the next generation of application-level data platforms and improving recent implementations. Hands-on experience with Apache Spark (PySpark, SparkSQL), Delta Lake, Iceberg, and Databricks is essential.


Responsibilities:

Design and develop data lakes, manage data flows that integrate information from various sources into a common data lake platform through an ETL Tool

Code and manage delta lake implementations on S3 using technologies like Databricks or Apache Hoodie

Triage, debug and fix technical issues related to Data Lakes

Design and Develop Data warehouses for Scale

Design and Evaluate Data Models (Star, Snowflake and Flattened)

Design data access patterns for OLTP and OLAP based transactions

Coordinate with Business and Technical teams through all the phases in the software development life cycle

Participate in making major technical and architectural decisions

Maintain and Manage Code repositories like Git


Must Have:

5+ Years of Experience operating on AWS Cloud with building Data Lake architectures

3+ Years of Experience with AWS Data services like S3, Glue, Lake Formation, EMR, Kinesis, RDS, DMS and Redshift

3+ Years of Experience building Data Warehouses on Snowflake, Redshift, HANA, Teradata, Exasol etc.

3+ Years of working knowledge in Spark

3+ Years of Experience in building Delta Lakes using technologies like Apache Hoodie or Data bricks

3+ Years of Experience working on any ETL tools and technologies

3+ Years of Experience in any programming language (Python, R, Scala, Java Bachelors degree in computer science, information technology, data science, data analytics or related field Experience working on Agile projects and Agile methodology in general


Good To Have:

Strong understanding of RDBMS principles and advanced data modelling techniques.

AWS cloud certification (e.g., AWS Certified Data Analytics Specialty) is a strong plus.


Key Skills:

Languages: Python, SQL, PySpark

Big Data Tools: Apache Spark, Databricks, Apache Hudi

Databricks on AWS

AWS Services: S3, Glue, Lake Formation, EMR, Kinesis, RDS, DMS, Redshift

Data warehouses: Snowflake, Redshift, HANA, Teradata, Exasol

Data Modelling: Star Schema, Snowflake Schema, Flattened Models

DevOps & CI/CD: Git, Agile Methodology, ETL Methodology

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Engineering - Software & QA
Role Category: Software Development
Role: Data Engineer
Employement Type: Full time

Contact Details:

Company: Celebal Technologies
Location(s): Hyderabad

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Keyskills:   Redshift Aws Databricks Unity Catalog Delta Live Table Pyspark Glue Lamda Teradata Python Autoloader Apache Spark

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Celebal Technologies

Company DetailsCelebal Technologies