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Data Engineer

Roles & Responsibilities

  • Experience in data engineering with emphasis on data pipelines, analytics and reporting
  • Exposure to the AWS Cloud Platform
  • Experience in SQL, data transformations, and troubleshooting across at least one database platform (Redshift, Amazon RDS, Cassandra, Snowflake, PostgreSQL, Databricks, etc.)
  • Experience designing and building data extraction, transformation, and loading processes by writing custom data pipelines

Requirements:

  • Work with the team to evaluate business needs and priorities, liaise with key business partners and address team needs related to data systems and management
  • Translate business requirements into technical specifications; establish and define details, definitions, and requirements of applications, components and enhancements
  • Develop data pipelines / APIs using a variety of tools, including but not limited to Python, SQL, Spark and various AWS services
  • Build large-scale batch and real-time data pipelines with data processing frameworks in AWS

Job description

As a Data Engineer, you will be part of a talented team of engineers responsible for the deployment and configuration of cloud resources to meet individual client business needs in AWS. Client engagements cover a wide variety of business requirements and require our engineers to adapt quickly and stay on top of recent cloud technology trends. Candidates should be able to identify and remediate issues within cloud-based systems, based on their knowledge of industry standards and best practices.

Responsibilities
  • Work with the team to evaluate business needs and priorities, liaise with key business partners and address team needs related to data systems and management 
  • Translate business requirements into technical specifications; establish and define details, definitions, and requirements of applications, components and enhancements
  • Participate in project planning; identifying milestones, deliverables and resource requirements; tracks activities and task execution
  • Generate design, development, test plans, detailed functional specifications documents, user interface design, and process flow charts for execution of programming
  • Develop data pipelines / APIs using a variety of tools, including but not limited to Python, SQL, Spark and various AWS services
  • Use an analytical, data-driven approach to drive a deep understanding of fast changing business 
  • Build large-scale batch and real-time data pipelines with data processing frameworks in AWS
  • Moving data from on-prem to cloud and cloud data conversions
Desired Skills & Experience
  • Experience in data engineering with an emphasis on data pipelines, analytics and reporting
  • Exposure to the AWS Cloud Platform
  • Experience in SQL, data transformations, and troubleshooting across at least one database Platform (Redshift, Amazon RDS, Cassandra, Snowflake, PostgreSQL, Databricks, etc.)
  • Experience in the design and build of data extraction, transformation, and loading processes by writing custom data pipelines
  • Experience in a scripting languages such as Python
  • Experience designing and building solutions utilizing various Cloud services such as EC2, S3, EMR, Kinesis, RDS, Redshift/Spectrum, Lambda, Glue, Athena, API gateway, etc.
Nice to Haves
  • AWS Certification - Solutions Architect Pro or Data Specialty
  • Machine Learning experience
  • Advanced GenAI experience


Compensation:
The expected base salary range for this position is $115,000 – $130,000 USD annually, plus eligibility for an annual performance bonus.

Actual compensation will depend on experience, skill set, and location.

Benefits:
We offer a comprehensive benefits package that includes medical, dental, and vision coverage, and paid time off.

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