AWS Data Engineer

Daily Tasks Performed: Develop and Maintain Data Integration Solutions: Design

and

implement data integration workflows

using

AWS Glue EMR ,

Lambda ,

Redshift Pyspark ,

Spark

and

Python

for

data processing large datasets Ensure data is

extracted, transformed, and loaded into target systems Build ETL pipelines using Iceberg Ensure Data Quality and Integrity:

Validate

and

cleanse data Ensure data quality

and

integrity

by

implementing monitoring ,

validation , and

error handling mechanisms

within

data pipelines Optimize Data Integration Processes:

Enhance the

performance ,

optimization

of

data workflows

to

meet SLAs , scalability of data integration

on AWS cloud infrastructure Data Analysis

and

Data Warehousing concepts

( star snowflake schema design ,

dimensional modeling , and

reporting enablement ) Resolve performance bottlenecks Optimize data processing to enhance Redshift's performance Refine integration processes Support Business Intelligence and Analytics:

Translate business requirements

to

technical specifications

and

coded data pipelines Ensure

integrated data for business intelligence

and

analytics Meet data requirements Maintain Documentation and Compliance:

Document all data integration processes

,

workflows

, and technical & system specifications. Ensure

compliance with data governance policies

, industry standards, and regulatory requirements.

What will this person be working on

Design

,

development

, and

management

of

data integration processes Integrating data from diverse sources ,

transforming it to meet business requirements , and

loading it into target systems

such as

data warehouses

or

data lakes

Position Success Criteria (Desired) - 'WANTS'

Bachelor's degree

in computer science, information technology, or a related field. A master's degree can be advantageous. 4-6+ years of experience

in

data engineering

,

database design

,

ETL processes Experience with

Iceberg 5+

in

programming languages

such as

PySpark ,

Python and SQL 5+ years of experience

with

AWS tools and technologies

( S3

,

EMR

,

Glue

,

Athena

,

RedShift

,

Postgres

,

RDS

,

Lambda

,

PySpark ) 3+ years of experience of working with databases data marts data warehouses ETL development

,

system integration

, and

CI CD implementation Experience in

complex database objects

to move the changed data across multiple environments Solid understanding of

data security

, privacy, and compliance. Participate in

agile development processes

including sprint planning stand-ups and retrospectives Provide technical guidance and mentorship to junior developers