Data Engineer

Required Skills : AWS Glue, Unix,Python,AWS Lambda,AWS EMR,AWS EC2,Spark,SQL,Amazon DynamoDB

Job summary :

As a Sr Data Engineer with 8-10 years of experience , you will play a pivotal role in analyzing business processes and leveraging technical skills to drive data-driven decisions.
You will work closely with cross-functional teams to ensure the successful implementation of solutions that align with business objectives.
Your expertise in Unix, Amazon DynamoDB, AWS EC2, AWS EMR, AWS Glue, AWS Lambda, SQL, Spark, and Python will be crucial in optimizing our data infrastructure and analytics cap

Responsibilities
Lead the analysis of business processes to identify opportunities for improvement and optimization.
Oversee the development and implementation of data-driven solutions to support business objectives.
Provide technical expertise in Unix, Amazon DynamoDB, AWS EC2, AWS EMR, AWS Glue, AWS Lambda, SQL, Spark, and Python to ensure robust data infrastructure.
Collaborate with cross-functional teams to gather and document business requirements.
Develop and maintain data models and databases to support analytics and reporting needs.
Utilize SQL and Python to extract, transform, and analyze data from various sources.
Implement data pipelines using AWS Glue and AWS Lambda to automate data processing workflows.
Optimize the performance of data processing tasks using Spark and AWS EMR.
Ensure data quality and integrity through rigorous testing and validation processes.
Create and maintain detailed documentation of data processes, models, and workflows.
Provide insights and recommendations based on data analysis to support strategic decision-making.
Train and mentor junior analysts on best practices and technical skills.
Stay updated with the latest industry trends and technologies to continuously improve data capabilities.

Qualifications
Possess a strong background in Unix, Amazon DynamoDB, AWS EC2, AWS EMR, AWS Glue, AWS Lambda, SQL, Spark, and Python.
Demonstrate excellent analytical and problem-solving skills.
Exhibit strong communication and collaboration abilities.
Show proficiency in developing and maintaining data models and databases.
Have experience in implementing data pipelines and automating workflows.
Display a keen attention to detail and commitment to data quality.
Be capable of providing actionable insights based on data analysis.
Have a track record of mentoring and training junior team members.
Stay abreast of industry trends and emerging technologies.