Data Engineer

Job Description

As a key contributor to the data engineering team, the candidate is expected to:

Build and deploy modular data pipeline components such as Apache Airflow DAGs, AWS Glue jobs, AWS Glue crawlers through a CI/CD process.
Translate Business or Functional Requirements to actionable technical build specifications.
Collaborate with other technology teams to extract, transform, and load data from a wide variety of data sources.
Work closely with product teams to deliver data products in a collaborative and agile environment.
Perform data analysis and onboarding activities as new data sources are added to the platform.
Proficient in data modeling techniques and concepts to support data consumers in designing the most efficient method of storage and retrieval of data.
Evaluate innovative technologies and tools while establishing standard design patterns and best practices for the team.

Qualifications

Required:

Experience in AWS Data processing, Analytics, and storage Services such as Simple Storage Service (s3), Glue, Athena and Lake Formation
Experience in extracting and delivering data from various databases such as MongoDB, DynamoDB, SnowFlake, Redshift, Postgres, RDS
Coding experience with Python, SQL, yaml, spark programming (pyspark)
Hands on experience with Apache Airflow as a pipeline orchestration tool
Experience in AWS Serverless services such as Fargate, SNS, SQS, Lambda
Experience in Containerized Workloads and using cloud services such as AWS ECS, ECR and Fargate to scale and organize these workloads.
Experience in data modeling and working with analytics teams to design efficient data structures.
Applied knowledge of working in agile, scrum, or DevOps environments and teams
Applied knowledge of modern software delivery methods like TDD, BDD, CI/CD
Applied knowledge of Infrastructure as Code (IAC)
Experience with development lifecycle (development, testing, documentation, and versioning)

Preferred

Any Graduate

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