About The Role ::
As a Data Engineer with AWS experience at [Your Company Name], you will play a crucial role in the design, development, and maintenance of our data infrastructure. Your work will empower data-driven decision-making and contribute to the success of our data-driven initiatives. Key Responsibilities:

Data Integration:Develop and maintain data pipelines to extract, transform, and load (ETL) data from various sources into AWS data stores for both batch and streaming data ingestion.

AWS Expertise:Utilize your expertise in AWS services such as Amazon EMR , S3, AWS Glue, Amazon Redshift, AWS Lambda, and more to build and optimize data solutions.

Data Modeling:Design and implement data models to support analytical and reporting needs, ensuring data accuracy and performance.

Data Quality:Implement data quality and data governance best practices to maintain data integrity.

Performance Optimization:Identify and resolve performance bottlenecks in data pipelines and storage solutions to ensure optimal performance.

Documentation:Create and maintain comprehensive documentation for data pipelines, architecture, and best practices.

Collaboration:Collaborate with cross-functional teams, including data scientists and analysts, to understand data requirements and deliver high-quality data solutions.

Automation:Implement automation processes and best practices to streamline data workflows and reduce manual interventions.

Must have: AWS, ETL, EMR, GLUE, Spark/Scala, Java, Python,
Good to have: Cloudera Spark, Hive, Impala, HDFS , Informatica PowerCenter, Informatica DQ/DG, Snowflake Erwin
Qualifications:

Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.

5 to 8 years of experience in data engineering, including working with AWS services.

Proficiency in AWS services like S3, Glue, Redshift, Lambda, and EMR.

Knowledge on Cloudera based hadoop is a plus.

Strong ETL development skills and experience with data integration tools.

Knowledge of data modeling, data warehousing, and data transformation techniques.

Familiarity with data quality and data governance principles.

Strong problem-solving and troubleshooting skills.

Excellent communication and teamwork skills, with the ability to collaborate with technical and non-technical stakeholders.

Knowledge of best practices in data engineering, scalability, and performance optimization.

Experience with version control systems and DevOps practices is a plus.

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AWS Lead Data Engineer-Sr. Software Engineer-Pune/Bangalore