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Senior Data Engineer-AWS

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Key Result Areas and Activities:

  • Technology Assessment and Design

  • Study existing technology landscape and understand current data integration frameworks and do impact assessment for the requirements.

  • Should be able to design complex Big Data use cases using AWS Services under guidance of Architect

  • Should be able to assist the architect in reasoning about various architecture choices in terms of cost, performance, durability.

  • Should be able to suggest optimizations in existing designs.

  • Ensure optimal balance between cost and performance.

  • Documentation and Stakeholder Communication

  • Project documentation, adheres to quality guidelines & schedules.

  • Works hand in hand with Architect & PM for successful delivery of project and provide estimation, scoping, scheduling assistance.

  • Articulate design decisions very clearly with stakeholders.

  • Perform Proof-of-Concepts and document all observations before proposing a new solution.

  • Conduct design review sessions with other teams and identify scope of improvement.

  • Process Improvement and Automation

  • Suggests automation to improve existing processes.

  • Assist junior Data Engineers by providing expert advice or troubleshooting steps whenever required.

  • Keep suggesting new ways to improve team productivity.

  • Training and Knowledge Sharing

  • Create technology-focused training plans whenever required.

  • Deliver technology-focused training sessions with team members whenever required.

  • Conduct Expert Knowledge Sharing sessions with Client Stakeholders whenever required.

  • Assist in designing case study documents whenever required.


Must-Have:

  • In-depth knowledge of the following AWS services: S3, EC2, EMR, Athena, AWS Glue, Lambda

  • Experience with at least one MPP database: AWS Redshift, Snowflake, SingleStore

  • Proficiency in Big Data technologies: Apache Spark, Databricks

  • Must have strong programming skills in Python

  • Responsible for building data pipelines in AWS And Databricks

  • Experience with Big Data table formats, such as Delta Lake (open source)

  • Must have very strong SQL skills

  • Experience with orchestration tools like Apache Airflow

  • Expertise in developing ETL workflows with complex transformations such as SCD, deduplications, aggregations, etc.

  • Should be a quick and self-learner, ready to adapt to new AWS services or Big Data technologies as required

  • Strong understanding of data warehousing concepts


Good to Have:

  • Cloud Databases – Snowflake, AWS Aurora

  • Big Data – Hadoop, Hive

  • Cloud Databases– AWS Aurora

  • Associate Level or Professional Level AWS Certification


Qualifications:

  • Overall 5+ years of IT Exp

  • 5+ years of relevant experience in AWS related project

  • Bachelor’s degree in computer science, engineering, or related field (master's degree is a plus)

  • Demonstrated continued learning through one or more technical certifications or related methods.

Years Of Exp

5 to 7 years

Location

India

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