AWS Data & Solution Engineer

EXL

United States

Who this role is best for

A natural match if you have experience designing enterprise data lakes and building data pipelines on AWS.

Best fit for

Candidates with experience in building enterprise data lakes on AWS and leading data engineering strategies
— “design and build solutions for one of our Fortune 500 Client programs, which aims towards building an Enterprise Data Lake on AWS Cloud platform”
Professionals skilled in Python and PySpark development with a track record in API service creation
— “You will be responsible for building API services using FastAPI or Flask frameworks”
Individuals who can influence executive-level decisions and drive long-term data planning
— “Represent team in executive meetings. Develop long-term data plans.”

Things to consider

The role likely involves working with large-scale clients and demands strategic leadership capabilities
— “design and build solutions for one of our Fortune 500 Client programs”
Candidates must meet a specific experience range of 4-6 years in data engineering or related fields
— “4-6 years of experience in data engineering or related field”

How to stand out

Highlight experience with enterprise-scale data lake architectures and AWS integration in your resume
— “aims towards building an Enterprise Data Lake on AWS Cloud platform”
Showcase leadership in data engineering strategy and cross-functional collaboration
— “Lead data engineering strategy across projects. Drive innovation in practices and optimization.”
Demonstrate your ability to present technical solutions to executive teams during interviews
— “Represent team in executive meetings.”
Emphasize your hands-on development experience with Python, PySpark, and API frameworks like FastAPI or Flask
— “primary skills on Python & PySpark development... building API services using FastAPI or Flask frameworks”
Include examples of long-term data planning and execution in your portfolio or resume
— “Develop long-term data plans.”

Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

Design and build solutions for Enterprise Data Lake
Develop data pipelines
Build API services
Represent team in executive meetings
Develop long-term data plans

Typical background

Computer ScienceData ScienceData Engineering

Skills & requirements

Required

AWS Cloud PlatformPythonPysparkAPI ServicesFastapiFlaskData EngineeringData PipelinesData IntegrationData Analytics

Preferred

Ai/ml Technologies

Stack & domain

PythonPysparkAWSData LakeData IntegrationData EngineeringData AnalyticsAPI ServicesFastapiFlaskLeadershipInnovationOptimizationTeamworkCommunicationProblem-solvingStrategic PlanningCloud Computing

About the role

Original posting from EXL

We are looking for an Sr AWS Data & Solutions Engineer with primary skills on Python & PySpark development who will be able to design and build solutions for one of our Fortune 500 Client programs, which aims towards building an Enterprise Data Lake on AWS Cloud platform, build Data pipelines by developing several AWS Data Integration, Engineering & Analytics resources. You will be responsible for building API services using FastAPI or Flask frameworks.
Lead data engineering strategy across projects. Drive innovation in practices and optimization. Represent team in executive meetings. Develop long-term data plans.
Graduate in Computer Science, Data Science, or related field. 4-6 years of experience in data engineering or related field.

Source: EXL careers