Senior Data Engineer

Requirements:

• 5+ years of experience in developing scalable Big Data applications or solutions on distributed platforms.

• 4+ years of experience working with distributed technology tools, including Spark, Python, Scala

• Working knowledge of Data warehousing, Data modelling, Governance and Data Architecture

• Proficient in working on Amazon Web Services (AWS) mainly S3, Managed Airflow, EMR/ EC2, IAM etc.

• Experience working in Agile and Scrum development processes.

• 3+ years of experience in Amazon Web Services (AWS) mainly S3, Managed Airflow, EMR/ EC2, IAM etc.

• Experience architecting data product in Streaming, Serverless and Microservices Architecture and

• platform.

• 3+ years of experience working with Data platforms, including EMR, Airflow, Databricks (Data Engineering &

Delta

• Experience with creating/ configuring Jenkins pipeline for smooth CI/CD process for Managed Spark jobs,

build Docker images, etc.

• Working knowledge of Reporting & Analytical tools such as Tableau, Quicksite etc.

Responsibilities:

• Developing scalable Big Data applications or solutions on distributed platforms.

• Proficient in working on Amazon Web Services (AWS) mainly S3, Managed Airflow, EMR/ EC2, IAM etc.

• Able to partner with others in solving complex problems by taking a broad perspective to identify

innovative solutions.

• Strong skills building positive relationships across Product and Engineering.

• Able to influence and communicate effectively, both verbally and written, with team members and

• business stakeholders

• Able to quickly pick up new programming languages, technologies, and frameworks.

• Experience working in Agile and Scrum development process.

• Experience working in a fast-paced, results-oriented environment.

• Experience in Amazon Web Services (AWS) mainly S3, Managed Airflow, EMR/ EC2, IAM etc.

• Experience working with Data Warehousing tools, including SQL database, Presto, and Snowflake

• Experience architecting data product in Streaming, Serverless and Microservices Architecture and

• platform.

• Experience working with Data platforms, including EMR, Airflow, Databricks (Data Engineering & Delta

• Lake components, and Lakehouse Medallion architecture), etc.

• Experience with creating/ configuring Jenkins pipeline for smooth CI/CD process for Managed Spark jobs,

• build Docker images, etc.

• Experience working with distributed technology tools, including Spark, Python, Scala

• Working knowledge of Data warehousing, Data modelling, Governance and Data Architecture

• Working knowledge of Reporting & Analytical tools such as Tableau, Quicksite etc.

• Demonstrated experience in learning new technologies and skills.