Tech Stack
Amazon RedshiftApacheAWSCloudETLPySparkPythonScalaSparkSQLTerraform
About the role
- Design and build next-gen data platforms and pipelines using Python, PySpark, or Scala
- Integrate data from diverse sources into centralised lakes and cloud platforms
- Create technology blueprints and engineering roadmaps for long-term transformation
- Ensure data security, governance, and compliance
- Deliver end-to-end solutions that meet business needs and minimise risk
- Build high-quality, scalable data products from scratch
- Communicate effectively with stakeholders and contribute to team-wide engineering practices
Requirements
- AWS Certified Data Engineer Associate with demonstrable experience in Data Engineering
- Strong expertise in Python, PySpark, SQL, Spark, Scala and distributed data processing
- Experience in AWS data platforms (Glue, Lambda, Redshift, Athena, Kinesis, EMR)
- Experience with AWS DataZone, Lake Formation, IAM, encryption
- Experience in using AI Powered coding Assistants like Cline, Roo and Aider
- Exposure to AWS Marketplace, API Gateway, and data monetization strategies
- Experience with Terraform, CloudFormation, GitOps, and serverless frameworks
- Ability to fine-tune ETL jobs, query performance, and cost efficiencies
- Experience with Snowflake, or Apache Iceberg
- Knowledge of data product thinking and data mesh principles
- Flexible working arrangements
- Professional development
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonPySparkSQLSparkScalaETLdata processingdata product thinkingdata mesh principlesdata governance
Soft skills
communicationstakeholder engagementteam collaborationproblem-solvingrisk management
Certifications
AWS Certified Data Engineer Associate