Be key to making our data lake more accessible and insightful breaking down the barriers to access by working on new data marts and designing data models that even the most basic SQL users can use
Build data pipelines with Spark or DBT
Use SQL to transform data into meaningful insights
Build and deploy infrastructure with Terraform
Implement DDL, DML with Iceberg
Do code reviews for your peers
Orchestrate your pipelines with DAGs on Airflow
Participate in SCRUM ceremonies (standups, backlogs, demos, retros, planning)
Secure data with IAM and AWS Lake formation
Deploy your changes with Jenkins and GitHub actions

Requirements

Proven experience as a Data Engineering using SQL and Python
Previous experience with data lakes in AWS, Glue Catalog and Athena (or equivalent)
Good experience with DBT
Capable of using popular data modelling tools to create a diagram of proposed tables to enable discussion
Good communicator and comfortable with presenting ideas and outputs to technical and non-technical users
Worked on Apache Airflow before to create DAGS
Ability to work within Agile, considering minimum viable products, story pointing and sprints

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLPythonSparkDBTTerraformDDLDMLIcebergApache Airflowdata modeling

Soft Skills

communicationpresentationcollaborationcode reviewAgile methodologySCRUMproblem-solvingteamworkadaptabilitycritical thinking