Job Description

Job summary

Our client is seeking a Senior Data Engineer to join our fast-growing team

The successful candidate will join the testing team to work on ETL and development tasks

This is an exciting and challenging opportunity to build out new pipelines combining and processing large amounts of structured data from a variety of sources with the power of PySpark at your fingertips

Key Responsibilities

Architect and build pipelines using AWS cloud computing solutions that make data available with robustness, maintainability, efficiency, scalability, availability and security

Develop Python and/or Spark (Preferably PySpark, but Spark-Scala is also good to have) code that implements complex data transformations

Design and maintain databases and APIs for storage and transmission of data between applications

Monitor pipelines in production (and develop tools to facilitate this)

Work collaboratively with other team members (brainstorming, troubleshooting, and code review)

Liaise with other development teams to ensure the integrity of data pipelines

Skills, Knowledge & Expertise

Skills:

Excellent Python and PySpark programming (including Pandas/PySpark dataframes, web and database connections)

Excellent understanding of ETL processes within Amazon Web Services (AWS)

Apache Spark, AWS Glue, Athena, S3, Step Functions, Lake Formation

Software development lifecycle best practices

Test-driven development

Serverless computing (AWS Lambda, API Gateway, SQS, SNS, EventBridge, S3, etc,)

SQL and NoSQL database design and management (DynamoDB, MySQL)

Strong SQL coding skills (Spark-SQL, Presto SQL, MySQL, etc,)

Infrastructure as code (CloudFormation)

Experience in Shell Scripting (preferably Linux)

Version control with Git/Github

Agile principles, processes and tools

Excellent written and verbal communication skills

Experience:

Designing, deploying and managing complex production data pipelines that interact with a range of data sources (file systems, web, database, users)

Strong experience with Amazon Web Services (AWS)

5 years’ work in data engineering field

At least 2 years' experience with PySpark and AWS data tools (particularly, Glue)

Knowledge:

Data modeling, data pipeline architecture, Big Data implementation

Software development lifecycle best practices

Financial knowledge would be an asset

Qualifications/Training:

Bachelor’s degree or equivalent in Computer Science or a related subject

What you’ll get in return

Competitive salary package

Private healthcare contribution

Annual pay review

Regular team socials

Working within a culture of innovation and collaboration

Opportunity to play a key role in a pioneering growth company

Company Laptop will be provided

More Info

Education